Vineeth N Balasubramanian

Publications

(* = Equal authorship)

2024

• A Gowtham Reddy, Vineeth N Balasubramanian, Detecting and Measuring Confounding Using Causal Mechanism Shifts, Proceedings of Neural Information Processing Systems (NeurIPS’24), Dec 2024

• Hari Chandana K, A Gowtham Reddy, Sai Srinivas K, Vineeth N Balasubramanian, Fine-Grained Visual Recognition in the Age of Multimodal LLMs, Workshop on Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning, Neural Information Processing Systems (NeurIPS’24), Dec 2024

• Aveen Dayal, Rishabh Lalla, Linga Reddy Cenkeramaddi, C Krishna Mohan, Abhinav Kumar, Vineeth N Balasubramanian, Improving Unsupervised Domain Adaptation: A Pseudo-Candidate Set Approach, Proceedings of European Conference on Computer Vision (ECCV’24), Oct 2024

• Prachi Garg, Joseph K J, Vineeth N Balasubramanian, Kenrick Kin, Shugao Ma, Fernando de la Torre, Adapting Human Action Models to New User Categories over Time, Proceedings of European Conference on Computer Vision (ECCV’24), Oct 2024

• Vaishnavi Khindkar, Vineeth N Balasubramanian, Chetan Arora, Anbumani Subramanian, C V Jawahar, Can Reasons Help Improve Pedestrian Intent Estimation? A Cross-Modal Approach, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’24), Oct 2024

• Sairam Rebbapragada VC, Pranoy Panda, V N Balasubramanian, C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’24), May 2024

• A Gowtham Reddy, Vineeth N Balasubramanian, NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’24), Feb 2024

• A Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin Godfrey, Varshaneya V, Satyanarayana Kar, Vineeth N Balasubramanian, Towards Learning and Explaining Indirect Causal Effects in Neural Networks, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’24), Feb 2024

• Sandesh Kamath, Amit Deshpande, Vineeth N Balasubramanian, Rethinking Robustness of Model Attributions, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’24), Feb 2024

• Bhat Dittakavi, Vikas Desai, Kamakshi Callepalli, Aleti Vardhan, Vineeth N Balasubramanian, CARE: Counterfactual-based Algorithmic Recourse for Explainable Pose Correction, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’24), Jan 2024

• Hiran Sarkar, Vishal Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth N Balasubramanian, Open-set Object Detection By Aligning Known Class Representations, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’24), Jan 2024

• Thrupthi Ann John, V. Balasubramanian, C V Jawahar, Explaining Deep Face Algorithms through Visualization: A Survey, IEEE Transactions on Biometrics, Behavior, and Identity Science, Vol 6:1, pg 15-29, Jan 2024 (Impact Factor: 5.81)

2023

• Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian, Mitigating the Effect of Incidental Correlations on Part-based Learning, Proceedings of Neural Information Processing Systems (NeurIPS’23), Dec 2023

• Aveen Dayal, Vimal K B, Linga Reddy Cenkeramaddi, C Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian, Margin-based Adversarial Learning for Domain Generalization, Proceedings of Neural Information Processing Systems (NeurIPS’23), Dec 2023

• Gaurav Bhatt*, Deepayan Das*, Leonid Sigal, Vineeth N Balasubramanian, Weakly-supervised Spatially Grounded Concept Learner for Few-Shot Learning, Proceedings of British Machine Vision Conference (BMVC’23), Nov 2023

• Purbayan Kar, Vishal Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth N Balasubramanian, Fiducial Focus Augmentation for Facial Landmark Detection, Proceedings of British Machine Vision Conference (BMVC’23), Nov 2023

• Vimal K B*, Saketh Bachu*, Tanmay Garg, Niveditha Lakshmi Narasimhan, Raghavan Konuru, V Balasubramanian, Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach, Proceedings of IEEE International Conference on Computer Vision (ICCV’23), Oct 2023

• Shubhra Aich, Jesus Ruiz-Santaquiteria, Prachi Garg, Zhenyu Lu, Joseph K J, Alvaro Fernandez Garcia, Kenrick Kin, Chengde Wan, Vineeth N Balasubramanian, Necati Cihan Camgoz, Shugao Ma, Fernando de la Torre, Data-Free Class-Incremental Hand Gesture Recognition, Proceedings of IEEE International Conference on Computer Vision (ICCV’23), Oct 2023

• Shivangana Rawat, Chaitanya Devaguptapu, V Balasubramanian, Partial Label Learning meets Active Learning: Enhancing Annotation Efficiency through Binary Questioning, Workshop on What do we need for successful domain generalization, International Conference on Machine Learning (ICML’23), Jul 2023 (also presented at Workshop on Knowledge and Logical Reasoning in the Era of Data-Driven Learning at ICML’23)

• Vaasudev Narayanan, Sai Srinivas Kancheti, V Balasubramanian, A Simple Test-Time Adaptation Method for Source-Free Domain Generalization, Workshop on Data-centric Machine Learning Research, International Conference on Learning Representations (ICLR’23), May 2023

• Gaurav Bhatt, V N Balasubramanian, Learning Style Subspaces for Controllable Unpaired Domain Translation, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’23), Jan 2023
  (Paper Link)
  

• Rebbapragada VC Sairam, Monish Keswani, Uttaran Sinha, Nishit Shah, V N Balasubramanian, ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’23), Jan 2023
  (arXiv)
  

• Surgan Jandial, Yash Khasbage, Arghya Pal, Balaji Krishnamurthy, V N Balasubramanian, RetroKD: Leveraging Past States for Regularizing Targets in Teacher-Student Learning, Proceedings of the 6th Joint International Conference on Data Science & Management of Data (ACM CODS-COMAD’23), Jan 2023
  (Paper Link)
  

2022

• V Balasubramanian, Toward Explainable Deep Learning, Communications of the ACM (India Region Special Issue), Vol. 65 No. 11, pg 68-69, Nov 2022
  (Paper link)
  

• Joseph K J, Sujoy Paul, Piyush Rai, Soma Biswas, Gaurav Aggarwal, V Balasubramanian, Novel Class Discovery without Forgetting, Proceedings of European Conference on Computer Vision (ECCV’22), Oct 2022
  

• Arjun Ashok, Joseph K J, V Balasubramanian, Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer, Proceedings of European Conference on Computer Vision (ECCV’22), Oct 2022 (Also presented at Workshop on Continual Learning in Computer Vision, IEEE-CVF Conference on Computer Vision and Pattern Recognition (CVPRW’22), Jun 2022)
  

• Surgan Jandial, Yash Khasbage, Arghya Pal, V Balasubramanian, Distilling the Undistillable: Learning from a Nasty Teacher, Proceedings of European Conference on Computer Vision (ECCV’22), Oct 2022
  

• Deepak Kumar Singh, Shyam Nandan Rai, Joseph K J, Rohit Saluja, V N Balasubramanian, Chetan Arora, Anbumani Subramanian, C V Jawahar, New Objects on the Road? No Problem, We’ll Learn Them Too, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’22), Oct 2022
  

• Sai Srinivas K*, A Gowtham Reddy*, Amit Sharma, V. Balasubramanian, Matching Learned Causal Effects of Neural Networks with Domain Priors, Proceedings of International Conference on Machine Learning (ICML’22), Jul 2022
  (arXiv)
  

• Anirban Sarkar, Anindya Sarkar, Deepak Vijayakeerthy, V. Balasubramanian, A Framework for Learning Ante-hoc Explainable Models via Concepts, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’22), Jun 2022
  (arXiv)
  

• Joseph K J, Salman Khan, Fahad Khan, V. Balasubramanian, Energy-based Latent Aligner for Incremental Learning, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’22), Jun 2022

• Hari Chandana K, Sumitra M, Shivam Chandhok, V. Balasubramanian, Unseen Classes at a Later Time? No Problem, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’22), Jun 2022

• Monish Keswani, Nishant Reddy S, Sriranjani R, V. Balasubramanian, Proto2Proto: Can you recognize the car, the way I do?, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’22), Jun 2022

• K J Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, V N Balasubramanian, Spacing Loss for Discovering Novel Categories, Workshop on Continual Learning in Vision, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’22), Jun 2022 (Best Paper Runner-Up Award)

• Piyushi Manupriya, Tarun Ram Menta, V. Balasubramanian, J Saketha Nath, Improving Attribution Methods by Learning Submodular Functions, Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS’22), Mar 2022

• A Gowtham Reddy, Benin Godfrey, V. Balasubramanian, On Causally Disentangled Representations, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’22), Feb 2022

• Saloni Dash, V Balasubramanian, Amit Sharma, Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (arXiv)
  

• Puneet Mangla, Shivam Chandhok, Vineeth N Balasubramanian, Fahad S Khan, COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (arXiv)
  

• Anirban Sarkar, Anindya Sarkar, V. Balasubramanian, Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (Also presented at Workshop on Adversarial Robustness In The Real World, IEEE-CVF International Conference on Computer Vision (ICCVW’21), Oct 2021)

• Puneet Mangla, Nupur Kumari, Mayank Singh, Balaji Krishnamurthy, Vineeth N Balasubramanian, Data InStance Prior (DISP) in Generative Adversarial Networks, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (arXiv)
  

• Prachi Garg, Rohit Saluja, V N Balasubramanian, Chetan Arora, Anbumani S, C. V. Jawahar, Multi-Domain Incremental Learning for Semantic Segmentation, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (arXiv)
  

• Shyam Nandan Rai, Chetan Arora, V N Balasubramanian, Anbumani S, Rohit Saluja, C. V. Jawahar, FLUID: Few-Shot Self-Supervised Image Deraining, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  

• Vaishnavi Khindkar, Chetan Arora, V N Balasubramanian, Anbumani S, Rohit Saluja, C. V. Jawahar, To mis-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object Detectors, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’22), Jan 2022
  (Code)

• Sandesh Kamath, Amit Deshpande, K V Subrahmanyam, V. Balasubramanian, Universalization of Any Adversarial Attack using Very Few Test Examples, Proceedings of ACM IKDD Joint International Conference on Data Science & Management of Data (CoDS-COMAD’22), Jan 2022. (Best Paper Award, Research Track)

2021

• Anindya Sarkar, Anirban Sarkar, Sowrya Gali, V. Balasubramanian, Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach, Proceedings of Neural Information Processing Systems (NeurIPS’21), Dec 2021
  

• Sandesh Kamath, Amit Deshpande, K V Subrahmanyam, V. Balasubramanian, Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks, Proceedings of Neural Information Processing Systems (NeurIPS’21), Dec 2021
  (arXiv)
  

• K J Joseph, Jathushan R, Salman Khan, Fahad Khan, V. Balasubramanian, Incremental Object Detection via Meta-Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 (accepted, to appear) (Impact Factor: 16.39)
  (arXiv)
  

• Shivam Chandhok, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Vineeth N Balasubramanian, Fahad Shahbaz Khan, Ling Shao, Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains, Proceedings of British Machine Vision Conference (BMVC’21), Nov 2021.
  (arXiv)
  

• Thrupthi A John, V. Balasubramanian, C V Jawahar, Canonical Saliency Maps: Decoding Deep Face Models, IEEE Transactions on Biometrics, Behavior, and Identity Science, 2021 (accepted, to appear)
  

• Ajay Kumar, Sai Vikas Desai, V. Balasubramanian, Wei Guo, Seishi Ninomiya, Uday Desai, P Rajalakshmi, Efficient Maize Tassel-Detection Method using UAV based Remote Sensing, Elsevier Remote Sensing Applications: Society and Environment, Vol 23: 100549, 2021

• A Gowtham Reddy, Benin Godfrey, V. Balasubramanian, CANDLE: An Image Dataset for CausalANalysis in DisentangLed REpresentations, Workshop on Causality in Vision, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’21), Jun 2021 (Best Paper Award)

• Joseph K J, Salman Khan, Fahad Khan, V. Balasubramanian, Towards Open-World Object Detection, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’21), Jun 2021 (Oral Paper)

• Puneet Mangla, Vedant Singh, Shreyas Havaldar, V. Balasubramanian, On the Benefits of Defining Vicinal Distributions in Latent Space, Workshop on Adversarial Machine Learning in Real-World Computer Vision Systems and Online Challenges, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’21), Jun 2021 (Best Paper Award)
  (Also presented at Workshops on Robust and Reliable Machine Learning in the Real World Workshop (RobustML) and Responsible AI at International Conference on Learning Representations (ICLR’21), May 2021)
  

• Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, V. Balasubramanian, Adversarial Robustness: A Neural Architecture Search Perspective, Workshops on Neural Architecture Search and From Shallow to Deep: Overcoming Limited and Adverse Data (S2D-OLAD) at International Conference on Learning Representations (ICLR’21), May 2021

• Adepu Ravi Sankar, Yash Khasbage, Rahul V, V. Balasubramanian, A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’21), Feb 2021

• Anindya Sarkar, Anirban Sarkar, V. Balasubramanian, Enhanced Regularizers for Attributional Robustness, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI’21), Feb 2021

• Shivam Chandhok, V Balasubramanian, Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’21), Jan 2021

2020

• Joseph K J, V. Balasubramanian, Meta-consolidation for Continual Learning, Proceedings of Neural Information Processing Systems (NeurIPS’20), Dec 2020
  

• Akshay Chandra, Sai Vikas D., Chaitanya D, V. Balasubramanian, Is There a Good Initial Pool for Active Learning?, Pre-Register Workshop, Neural Information Processing Systems (NeurIPS Workshops’20), Dec 2020
  

• Vaibhav Sinha, Sneha Kudugunta, Adepu Ravi Sankar, Surya Teja Chavali, V. Balasubramanian, DANTE: Deep Alternations for Training Neural Networks, Elsevier Neural Networks, Jul 2020. (Impact Factor: 5.5)

• Udit Maniyar, Joseph K J, Aniket Deshmukh, Urun Dogan, V. Balasubramanian, Zero-shot Domain Generalization, Proceedings of British Machine Vision Conference (BMVC’20), Sep 2020.
  (Also presented at Workshop on Visual Learning with Limited Labels, IEEE-CVF International Conference on Computer Vision and Pattern Recognition (CVPR’20), Jun 2020)

• Shyam Nandan R., Anbumani S., V. Balasubramanian, C V Jawahar, Spatial Feedback Learning to Improve Semantic Segmentation in Hot Weather, Proceedings of British Machine Vision Conference (BMVC’20), Sep 2020.
  

• Mayank S., Nupur K., Puneet M., Abhishek S., V. Balasubramanian, Balaji K., Attributional Robustness Training using Input-Gradient Spatial Alignment, Proceedings of European Conference on Computer Vision (ECCV’20), Aug 2020.
  

• Akshay Chandra, Sai Vikas D., S. Ninomiya, Wei Guo, V. Balasubramanian, EasyRFP: An Easy to Use Edge Computing Toolkit for Real-time Field Phenotyping, European Conference on Computer Vision (ECCV’20 Demos), Aug 2020.
  (Also presented at the Workshop on Computer Vision Problems in Plant Phenotyping-CVPPP at ECCV’20, Aug 2020)
  

• Puneet M., Vedant S., V. Balasubramanian, On Saliency Maps and Adversarial Robustness, Proceedings of European Conference of Machine Learning and and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’20), Ghent, Belgium, Sep 2020.
  

• Surgan J, Ayush C, Mausoom S, Piyush G, Balaji K, V. Balasubramanian, Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks, Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’20), San Diego, Aug 2020.
  

• Piyushi M., Saketha Nath J, V. Balasubramanian, SEA-NN: Submodular Ensembled Attribution for Neural Networks, Workshop on Human Interpretability in Machine Learning (WHI 2020) and Workshop on Extending Explainable AI Beyond Deep Models and Classifiers (XXAI), International Conference on Machine Learning (ICML’20), Jul 2020.

• Sai Vikas Desai, V. Balasubramanian, Towards Fine-grained Sampling for Active Learning in Object Detection, Workshop on Visual Learning with Limited Labels, IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR’20), Jun 2020.

• Akshay Chandra, Sai Vikas D., S. Ninomiya, Wei Guo, V. Balasubramanian, Active Learning with Point Supervision for Cost-Effective Panicle Detection in Cereal Crops, BMC Plant Methods, 2020. (Impact Factor: 4.5)
  (arXiv)

• Chandra, A.L., Desai, S. V., Balasubramanian, V. N., Guo, W, Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey, Journal of Advanced Computing and Communications, Apr 2020.
  

• Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Balaji K, V N Balasubramanian, Charting the Right Manifold: Manifold Mixup for Few-shot Learning, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’20), Mar 2020.
  (Also presented at the NeurIPS 2019 Workshop on Meta-Learning)
  (arXiv) (Code)

• Dikshant Gupta, Aditya A, Nehal M, V. Balasubramanian, C V Jawahar, Multi-Space Approach to Zero-Shot Object Detection, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’20), Mar 2020.

• Harshitha M., V. Balasubramanian, A Little Fog for a Large Turn, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’20), Mar 2020.
  (Code and Paper)

• Shyam Rai, Anubani Subramanian, V. Balasubramanian, C V Jawahar, Munich to Dubai: How far is it for Semantic Segmentation?, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’20), Mar 2020.

• Saurabh R, Rahul B, V N Balasubramanian, Nageswara Rao N, Sujit Gujar, C V Jawahar, Human Machine Collaboration for Face Recognition, Proceedings of ACM IKDD Joint International Conference on Data Science & Management of Data (CoDS-COMAD’20), Jan 2020. (Best Paper Award Runner-up)

2019

• Sai Vikas D., V. Balasubramanian, T. Fukatsu, S. Ninomiya, Wei Guo, Automatic estimation of heading date of paddy rice using deep learning, BMC Plant Methods, 2019. (Impact Factor: 4.5)
  (arXiv)

• Sai Vikas D., Akshay C., Wei Guo, S. Ninomiya, V. Balasubramanian, An Adaptive Supervision Framework for Active Learning in Object Detection, in Proceedings of the British Machine Vision Conference (BMVC’19), Sep 2019.

• Joseph K J, Vamshi Teja R, Krishnakant Singh, V. Balasubramanian, Submodular Batch Selection for Training Deep Neural Networks, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI’19), Aug 2019. (Also presented at the Negative Dependence in ML Workshop at ICML 2019)

• Nupur Kumari, Abhishek Sinha, Mayank Singh, Harshitha Machiraju, Balaji Krishnamurthy, V. Balasubramanian, Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI’19), Aug 2019.

• Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, V. Balasubramanian, Neural Network Attributions: A Causal Perspective, Proceedings of International Conference on Machine Learning (ICML’19), Jun 2019.
  (arXiv) (Code)

• Uttaran Sinha, Saurabh Joshi, V. Balasubramanian, Defending Deep Neural Networks against Structural Perturbations, Workshop on Uncertainty and Robustness in Deep Learning, International Conference on Machine Learning (ICML’19), Jun 2019.

• Arghya Pal, V. Balasubramanian, Zero-shot Task Transfer, Proceedings of the IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR’19), Jun 2019. (Oral Paper)
  (arXiv)

• Chaitanya Devaguptapu, Ninad Akolekar, Manuj Sharma, V. Balasubramanian, Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery, Workshop on Perception beyond the Visible Spectrum, IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR’19), Jun 2019.

• Mayank Singh, Abhishek Sinha, Nupur Kumari, Balaji Krishnamurthy, Harshitha Machiraju, V N Balasubramanian, Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models, Workshop on Safe Machine Learning, International Conference on Learning Representations (ICLR’19), May 2019.

• Lovish Chum, Anbumani S., V. Balasubramanian, C. V. Jawahar, Beyond Supervised Learning: A Computer Vision Perspective, Journal of the Indian Institute of Science, pp 1-23, Feb 2019.
  

• Joseph K.J, Arghya Pal, S. Rajanala, V. Balasubramanian, C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’19), Jan 2019.
  (arXiv)

• Tejaswi K., Nagendar G., Guruprasad Hegde, V. Balasubramanian, C. V. Jawahar, Region-Based Active Learning for Efficient Labeling in Semantic Segmentation, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’19), Jan 2019.

2018

• Parikshit S., V. Balasubramanian, P.J. Narayanan, RefocusGAN: Scene Refocusing using a Single Image, in Proceedings of the European Conference on Computer Vision (ECCV’18), Sep 2018.

• Joseph K.J., R. Patel, U. Gupta, A. Srivastava, V. Balasubramanian, MASON: A Model AgnoStic ObjectNess Framework, in Workshop On Autonomous Navigation in Unconstrained Environments, European Conference on Computer Vision, Workshop Proceedings (ECCV-W), Sep 2018.
  (arXiv) (Github)

• Zhu Pengfei, Wen Longyin, Du Dawei, Nehal M., Naveen Kumar, Joseph K.J., V. Balasubramanian, et al. VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results, European Conference on Computer Vision, Workshop Proceedings (ECCV-W), Sep 2018.
  

• G. Nagendar, V. Balasubramanian, C. V. Jawahar, Neuro-IoU: Learning a Surrogate Loss for Semantic Segmentation, in Proceedings of the British Machine Vision Conference (BMVC’18), Sep 2018.

• N. Agarwal, V. Balasubramanian, C.V. Jawahar, Improving Multiclass Classification by Deep Networks using DAGSVM and Triplet Loss, Pattern Recognition Letters, 2018 (accepted).

• Vaibhav Sinha, Sukrut Rao, V. Balasubramanian, Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification, in Workshop on Issues of Sentiment Discovery and Opinion Mining at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), London, UK, Aug 2018.
  (arXiv) (Github)

• A. Gupta, A. DCunha, K. Awasthi, V. Balasubramanian, DAiSEE: Towards User Engagement Recognition in the Wild, in 4th Vision Meets Cognition Workshop at IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, Jun 2018.
  (arXiv) (Web) (Media)

• A. Ravi Sankar, Vishwak S., V. Balasubramanian, On the Analysis of Trajectories of Gradient Descent in the Optimization of Deep Neural Networks, in Workshop on Theory of Deep Learning and Workshop on Non-Convex Optimization at International Conference on Machine Learning (ICML), Stockholm, Sweden, Jul 2018.
  (arXiv)

• Arghya Pal, V. Balasubramanian, Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data, in Proceedings of the IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR’18), Jun 2018.
  (arXiv)

• Anirban Sarkar, Aditya Chattopadhyay, Prantik Howlader, V. Balasubramanian, Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep Convolutional Networks, Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV’18), Mar 2018.
  (arXiv) (Github)

• Supriya P., Himangi Mittal, Manish Gupta, V. Balasubramanian, STWalk: Learning Trajectory Representations in Temporal Graphs, Proceedings of ACM IKDD Joint International Conference on Data Science & Management of Data (CoDS-COMAD’18), Jan 2018.
  (arXiv)

• A. Ravi Sankar, V. Balasubramanian, Are Saddles Good Enough for Deep Learning, arXiv:1706.02052, Proceedings of ACM IKDD Joint International Conference on Data Science & Management of Data (CoDS-COMAD’18), Jan 2018.
  (arXiv)

• Vishwak S., A. Ravi Sankar, V. Balasubramanian, ADINE: An Adaptive Momentum Method for Stochastic Gradient Descent, Proceedings of ACM IKDD Joint International Conference on Data Science & Management of Data (CoDS-COMAD’18), Jan 2018.
  (arXiv)

2017

• Swetha S., V. Balasubramanian, C. V. Jawahar, Sequence to Sequence learning for Pose Correction in Videos, Proceedings of 4th Asian Conference on Pattern Recognition (ACPR’17), Nov 2017.

• G. Mittal, T. Marwah, V. Balasubramanian, Attentive Semantic Video Generation using Captions, Proceedings of IEEE International Conference on Computer Vision (ICCV’17), Oct 2017.
  (arXiv) (Github)

• T. Marwah, G. Mittal, V. Balasubramanian, Sync-DRAW: Automatic Video Generation using Deep Recurrent Attentive Architectures, Proceedings of ACM International Conference on Multimedia (ACM MM’17), Oct 2017. (Oral Paper, Acceptance Rate: 7.5%)
  (arXiv) (Github)

• D. Bhatt, D. Sodhi, A. Pal, V. Balasubramanian, M. Krishna, Have I Reached the Intersection?, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’17), Sep 2017.

2016

• S. Pandhre, M. Gupta, V. Balasubramanian, Community-based Outlier Detection for Edge-Attributed Graphs, arXiv:1612.09435, Dec 2016.
  (arXiv)

• B Akilesh, T. Marwah, V. Balasubramanian, K. Rajamani, On the Relevance of Very Deep Networks for Diabetic Retinopathy Diagnostics, IBM Collaborative Academia Research Exchange (I-CARE) Conference, Bangalore, Oct 2016.

• B. B. Sau, V. Balasubramanian, Deep Model Compression: Distilling Knowledge from Noisy Teachers, arXiv:1610.09650, Oct 2016.
  (arXiv)

• S. Manocha, A Ravi Sankar, V. Balasubramanian, Dissimilarity-based Contrastive Divergence for Anomaly Detection, 2nd Indian Workshop on Machine Learning, Kanpur, Jul 2016.

• A Kamath, A Biswas, V. Balasubramanian, A Crowdsourced Approach to Student Engagement Recognition in e-Learning Environments, IEEE Winter Conference on Applications of Computer Vision (WACV’16), Lake Placid, NY, Mar 2016.

• D Singh, V. Balasubramanian, C. V. Jawahar, Fine-Tuning Human Pose Estimations in Videos, IEEE Winter Conference on Applications of Computer Vision (WACV’16), Lake Placid, NY, Mar 2016.

• A. Pal, B.K. Khonglah, S. Mandal, H. Choudhury, S.R.M. Prasanna, H.L. Rufiner, V. Balasubramanian, Online Bengali Handwritten Numerals Recognition Using Deep Autoencoders, National Conference on Communications (NCC), Mar 2016.

2015

• A Ravi Sankar, V. Balasubramanian, Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models, 7th Asian Conference on Machine Learning (ACML), Hong Kong, 2015.

• S. Chakraborty, V. Balasubramanian, Q. Sun, S. Panchanathan, J. Ye, Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), Oct 2015, 37(10), pp 1945-58.

• S. Chakraborty, V. Balasubramanian, A. Ravi Sankar, S. Panchanathan, J. Ye, BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification, In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’15), 2015, pp 99-108.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Adaptive Batch Mode Active Learning, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), Aug 2015, vol.26, no.8, pp.1747-1760.

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Conformal Predictions for Information Fusion, Annals of Mathematics and Artificial Intelligence (AMAI), Jun 2015, Vol 74, Issue 1, pp 45-65.

• Sai Rajeshwar, A Ravi Sankar, V. Balasubramanian, C.D. Sudheer, Scaling up the training of Deep CNNs for Human Action Recognition, 4th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (in conjunction with IPDPS 2015), Hyderabad, India, 2015, pp 1172-1177.

• R. Jaiswal, V. Balasubramanian, Model Selection Using Efficiency of Conformal Predictors, 3rd International Symposium on Learning and Data Sciences (SLDS 2015), Royal Holloway University of London, Apr 2015, pp 291-300.

2014

• Sai Rajeshwar, A Ravi Sankar, V. Balasubramanian, C.D. Sudheer, Parallel Learning of Deep Convolutional Neural networks and its Application to Action Recognition, IEEE International Conference on High Performance Computing - Student Research Symposium, Goa, India, 2014. (NVIDIA Award for Best Paper using GPU Technologies)

2013

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Generalized batch mode active learning for face-based biometric recognition, Pattern Recognition, 46:2, 2013.

• S. Chakraborty, J. Zhou, V. Balasubramanian, S. Panchanathan, I. Davidson, J. Ye, Active Matrix Completion, In Proceedings of the IEEE International Conference on Data Mining (ICDM’13), Dallas, USA, pp 81-90, Dec 2013.

• P. Lade, V. Balasubramanian, S. Panchanathan, Probabilistic Topic Models for Human Emotion Analysis, in Proceedings of the Workshop on Topic Models: Computation, Application and Evaluation at Neural Information Processing Systems (NIPS), Lake Tahoe, USA, Dec 2013.

• V. Balasubramanian, A. Baker, M. Yanez, S. Chakraborty, S. Panchanathan, PyCP: An Open-Source Conformal Predictions Toolkit, in Proceedings of Artificial Intelligence Applications and Innovations (Workshop on Conformal Prediction and Its Applications), vol 412, pp 361-370, Paphos, Cyprus, Oct 2013.

• P. Lade, V. Balasubramanian, S. Panchanathan, Detection of Changes in Human Affect Dimensions using an Adaptive Temporal Topic Model, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME), pp 1-6, San Jose, USA, Jul 2013.

• H. Venkateswara, V. Balasubramanian, S. Panchanathan, Multiresolution Match Kernels for Gesture Video Classification, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME), pp 1-4, San Jose, USA, Jul 2013.

• P. Lade, V. Balasubramanian, S. Panchanathan, Latent Facial Topics for Affect Analysis, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME) Workshop on Affective Analysis in Multimedia, pp 1-6, San Jose, USA, Jul 2013.

2012

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Batch Mode Active Learning for Multimedia Pattern Recognition, PhD Workshop on Multimedia Computing Research, in Proceedings of IEEE International Symposium on Multimedia (ISM’12), pp 489-490, Irvine, USA, Dec 2012.

• S. Panchanathan, T. McDaniel, V. Balasubramanian, Person-Centered Accessible Technologies: Improved Usability and Adaptation through Inspirations from Disability Research, in Proceedings of the International Workshop on User Experience in e-Learning and Augmented Technologies in Education Proceedings at ACM Multimedia (ACM MM’12), pp 1-6, Nara, Japan, Nov 2012.

• M. Alzubaidi, V. Balasubramanian, A. Patel, S. Panchanathan, J. A. Black, Efficient Atypicality Detection in Chest Radiographs, in Proceedings of 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), pp 193-198, Montreal, Canada, Jul 2012.

• M. Alzubaidi, V. Balasubramanian, A. Patel, S. Panchanathan, J. A. Black, A Novel Semi-Transductive Learning Framework for Atypicality Detection in Chest Radiographs, in Proceedings of SPIE Conference on Medical Imaging, Vol 8315 (Computer-Aided Diagnosis), 83153A, San Diego, USA, Feb 2012.

2011

• S. Nataraju, V. Balasubramanian, S. Panchanathan, An Integrated Approach to Visual Attention Modeling for Saliency Detection in Videos, In Machine Learning for Vision-based Motion Analysis: Advances in Pattern Recognition, Part 3, pp 181-214, Liang Wang, Guoying Zhao, Li Cheng, Matti Pietikainen (Eds.), Springer-Verlag London, 2011.

• S. Chakraborty, H. Venkateswara, V. Balasubramanian, S. Panchanathan, Active Batch Selection for Fuzzy Classification in Facial Expression Recognition, in Proceedings of 10th International Conference on Machine Learning and Applications (ICMLA’11), vol.1, pp.241-246, Hawaii, USA, Dec 2011.

• R. Chattopadhyay, S. Chakraborty, V. Balasubramanian, S. Panchanathan, Optimization-based Domain Adaptation towards Person-Adaptive Classification Models, in Proceedings of 10th International Conference on Machine Learning and Applications (ICMLA’11), vol.1, pp.476-483, Hawaii, USA, Dec 2011.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Optimal Batch Selection for Active Learning in Multi-label Classification, In Proceedings of the 19th ACM International Conference on Multimedia (ACM MM’11), pp 1413-1416, Scottsdale, USA, Nov 2011.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Dynamic Batch Mode Active Learning via L1 Regularization, in Proceedings of the National Conference on Artificial Intelligence (AAAI’11), Vol 2, pp 1764-1765, San Francisco, USA, Aug 2011.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Dynamic Batch Mode Active Learning, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’11), pp 2649-2656, Colorado Springs, USA, Jun 2011.

• S. Panchanathan, S. Krishna, V. Balasubramanian, Human-Centered Multimedia Computing: Inspirations through Enriching the Lives of Individuals with Sensory, Motor, Perceptual and Cognitive Disabilities, in Proceedings of the 7th International Conference on Trends in Industrial Measurements and Automation (TIMA 2011), pp 1-6, Chennai, India, Jan 2011.

2010

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Multiple Kernel Learning for Efficient Conformal Predictions, in Proceedings of the Workshop on New Directions in Multiple Kernel Learning at Neural Information Processing Systems (NIPS), Whistler, Canada, Dec 2010.

• V. Balasubramanian, S. Chakraborty, S. Krishna, S. Panchanathan, Enhancing Social Interactions of Individuals with Visual Impairments: A Case Study for Assistive Machine Learning, in Proceedings of the Workshop on Machine Learning for Assistive Technologies at Neural Information Processing Systems (NIPS), Whistler, Canada, Dec 2010.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, An Optimization Based Framework for Dynamic Batch Mode Active Learning, in Proceedings of the 3rd International Workshop on Optimization for Machine Learning at Neural Information Processing Systems (NIPS), Whistler, Canada, Dec 2010.

• V. Balasubramanian, J. Ye, S. Chakraborty, S. Panchanathan, Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework, in Proceedings of the 9th International Conference on Machine Learning and Applications (ICMLA’10), IEEE Computer Society, pp 235-242, Washington DC, USA, Dec 2010.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Dynamic Batch Size Selection for Batch Mode Active Learning in Biometrics, in Proceedings of the 9th International Conference on Machine Learning and Applications (ICMLA’10), IEEE Computer Society, pp 15-22, Washington DC, USA, Dec 2010.

• S. Krishna, V. Balasubramanian, S. Panchanathan, Enriching Social Situational Awareness in Remote Interactions: Insights and Inspirations from Disability Focused Research, in Proceedings of the ACM International Conference on Multimedia (ACM MM’10), pp 1275-1284, Firenze, Italy, Oct 2010.

• S. Marcel, C. McCool, S. Chakraborty, V. Balasubramanian, S. Panchanathan, J.Nolazco, L. Garcia, R. Aceves, et al., On the results of the first mobile biometry (MOBIO) face and speaker verification evaluation, in Proceedings of the 20th International Conference on Pattern Recognition (ICPR’10), pp 210-225, Istanbul, Turkey, Aug 2010.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Learning from Summaries of Videos: Applying Batch Mode Active Learning to Face-based Biometrics, Workshop on Biometrics, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR’10), pp 130-137, San Francisco, USA, Jun 2010.

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Batch Mode Active Learning for Biometric Recognition, Proceedings of SPIE International Conference on Biometric Technology for Human Identification, SPIE Defense, Security & Sensing, Vol 7667, B. V. K. Vijaya Kumar, Salil Prabhakar, Arun A. Ross (Eds.), 76670W, Orlando, USA, Apr 2010.

• M. Alzubadi, V. Balasubramanian, J. A. Black, A. Patel, S. Panchanathan, What Catches a Radiologist’s Eye? A Comprehensive Comparison of Feature Types for Saliency Prediction, in Proceedings of SPIE Conference on Medical Imaging, Vol 7624 (Computer-Aided Diagnosis), Nico Karssemeijer, Ronald M. Summers (Eds.), 76240W, San Diego, USA, Feb 2010.

2009

• S. Krishna, V. Balasubramanian, J. Black, S. Panchanathan, Person-Specific Characteristic Feature Selection for Face Recognition, Biometrics: Theory, Methods, and Applications, pp 113-141, N. V. Boulgouris, K. N. Plataniotis and E. Micheli-Tzanakou (Eds.), Wiley Publications, 2009.

• V. Balasubramanian, S. Chakraborty, S. Krishna, S. Panchanathan, Human-Centered Machine Learning in a Social Interaction Assistant for Individuals with Visual Impairments, in Proceedings of the Symposium on Assistive Machine Learning for People with Disabilities at Neural Information Processing Systems (NIPS’09), Vancouver, Canada, Dec 2009.

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Online Active Learning using Conformal Predictions, in Proceedings of the Workshop on Analysis and Design of Algorithms for Interactive Machine Learning at Neural Information Processing Systems (NIPS’09), Vancouver, Canada, Dec 2009.

• S. Nataraju, V. Balasubramanian, S. Panchanathan, Learning Attention Based Saliency in Videos from Human Eye Movements, in Proceedings of the International Workshop on Motion and Video Computing (WMVC), IEEE Computer Society, pp 134-139, Snowbird, USA, Dec 2009.

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Generalized Query by Transduction for Online Active Learning, Workshop on Online Learning for Computer Vision, in Proceedings of the IEEE Computer Society International Conference on Computer Vision Workshops (ICCV’09), pp 1378-1385, Kyoto, Japan, Oct 2009.

• V. Balasubramanian, R. Gouripeddi, J. Vermillion, A. Bhaskaran, R. Siegel, S. Panchanathan, Support Vector Machine Based Conformal Predictors for Risk of Complications Following a Coronary Drug Eluting Stent Procedure, in Proceedings of IEEE Computers in Cardiology, pp 5-8, Park City, USA, Sep 2009.

• R. Gouripeddi, V. Balasubramanian, J. Harris, A. Bhaskaran, R. Siegel, S. Panchanathan, Ranking Predictors of Complications following a Drug Eluting Stent Procedure using Support Vector Machines, in Proceedings of IEEE Computers in Cardiology, pp 345-348, Park City, USA, Sep 2009.

• R. Gouripeddi, V. Balasubramanian, J. Harris, A. Bhaskaran, R. Siegel, S. Panchanathan, Predicting risk of complications following a Drug Eluting Stent Procedure: a SVM approach for imbalanced data, in Proceedings of 22nd IEEE International Symposium on Computer-Based Medical Systems, pp 1-7, Albuquerque, USA, Aug 2009.

2008

• V. Balasubramanian, S. Panchanathan, Biased Manifold Embedding: Supervised Isomap for Person-Independent Head Pose Estimation, In Computer Vision and Computer Graphics: Theory and Applications, Vol 21, pp 177-188, Jose Braz, Alpesh Ranchordas, Helder J. Araujo, Joao Madeiras Pereira (Eds.), Springer Berlin Heidelberg, 2008.

• V. Balasubramanian, S. Krishna, S. Panchanathan, Person-independent head pose estimation using biased manifold embedding, EURASIP Journal on Advanced Signal Processing, pp 63:1-63:15, Hindawi Publishing Corporation, 2008.

• S. Panchanathan, N. C. Krishnan, S. Krishna, T. McDaniel, V. N. Balasubramanian, Enriched Human-Centered Multimedia Computing through Inspirations from Disabilities and Deficit-Centered Computing Solutions, in Proceedings of the 3rd ACM International Workshop on Human-Centered Computing, (ACM MM’08), pp 35-42, Vancouver, Canada, Oct 2008.

• T. McDaniel, S. Krishna, V. Balasubramanian, D. Colbry, S. Panchanathan, Using a haptic belt to convey non-verbal communication cues during social interactions to individuals who are blind, in Proceedings of IEEE International Workshop on Haptic Audio visual Environments and Games (HAVE), pp.13-18, Ottawa, Canada, Oct 2008.

• S. Krishna, D. Colbry, J. Black, V. N. Balasubramanian, S. Panchanathan, A Systematic Requirements Analysis and Development of an Assistive Device to Enhance the Social Interaction of People Who are Blind or Visually Impaired, in Proceedings of the European Conference on Computer Vision Workshop on Computer Vision Applications for the Visually Impaired (ECCV’08), Marseille, France, Oct 2008.

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Multiple Cue Integration in Transductive Confidence Machines for Head Pose Classification, Workshop on Online Learning for Classification, in Proceedings of the IEEE Computer Vision and Pattern Recognition Workshops (CVPR’08), pp 1-8, Anchorage, USA, Jun 2008.

• S. Krishna, S. Panchanathan, T. Hedgpeth, C. Juillard, V. Balasubramanian, N. C. Krishnan, A Wearable Wireless RFID System for Accessible Shopping Environments, in Proceedings of the ICST 3rd International Conference on Body Area Networks (BodyNets’08), pp 29:1-29:8, Tempe, USA, Mar 2008.

• S. Panchanathan, S. Krishna, J.A. Black, V. Balasubramanian, Human-Centered Multimedia Computing: A New Paradigm for the Design of Assistive and Rehabilitative Environments, in Proceedings of the International Conference on Signal Processing, Communications and Networking (ICSCN’08), pp 1-7, Chennai, India, Jan 2008.

2007

• V. N. Balasubramanian, J. Ye, S. Panchanathan, Biased Manifold Embedding: A framework for Person-Independent Head Pose Estimation, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07), pp 1-7, Minneapolis, USA, Jun 2007.

• V. N. Balasubramanian, S. Panchanathan, Biased Manifold Embedding for Person-Independent Head Pose Estimation, in Proceedings of the 2nd International Conference on Computer Vision Theory and Applications, pp 76-84, Alpesh Ranchordas, Helder Araujo, Jordi Vitria (Eds.), Barcelona, Spain, Mar 2007.

2006 and prior

• K. Kahol, N. C. Krishnan, V. N. Balasubramanian, S. Panchanathan, M. Smith, J. Ferrara, Measuring movement expertise in surgical tasks, in Proceedings of the 14th Annual ACM Conference on Multimedia (ACM MM’06), pp 719-722, Santa Barbara, USA, Oct 2006.

• N.B. Vineeth, B. Krishnamoorthy, G.V. Prabhakara Rao, Mosaicing of MPEG compressed video: a unified approach, in Proceedings of the SPIE International Conference on Optical Science and Engineering, Vol 5558 (Applications of Digital Image Processing), 847, Denver, USA, Aug 2004.

OTHER

• S. Chakraborty, V. Balasubramanian, S. Panchanathan, Batch Mode Active Learning for Multimedia Pattern Recognition, 7th Annual Machine Learning Symposium, New York Academy of Sciences, New York, USA, Oct 2012.

• V. Balasubramanian, S. Chakraborty, S. Panchanathan, Confidence Estimation in Pattern Classification: An Analysis with Head Pose Estimation, Technical Report TR-09-12, School of Computing and Informatics, Arizona State University, Jul 2009.

• S. Krishna, T. McDaniel, V. Balasubramanian, D. Colbry, S. Panchanathan, Haptic Belt for Delivering Nonverbal Cues to People who are Blind/Visually Impaired, 24th Annual International Technology and Persons with Disabilities Conference (CSUN’09), Los Angeles, USA, Mar 2009.

• S. Krishna, V. Balasubramanian, N. C. Krishnan, T. Hedgpeth, The iCARE Ambient Interactive Shopping Environment, CSUN's 23rd Annual International Technology and Persons with Disabilities Conference (CSUN’08), Los Angeles, USA, Mar 2008.