Publications and Reports

Book Chapters

• S. Anand , S. Mittal, P. Meer, "Robust Estimation for Computer Vision using Grassmann Manifolds", Riemannian Computing in Computer Vision, Co-editors: P.K. Turaga and A. Srivastava. Springer. Chapter 6. 2015

Selected Refereed Journals

• N. Mehrotra, N. Agarwal, P. Gupta, S. Anand, D. Lo, and R. Purandare, "Modeling Functional Similarity in Source Code with Graph-Based Siamese Networks", IEEE Transactions on Software Engineering, 2021, DOI: 10.1109/TSE.2021.3105556.ArXiv pre-print.
• A. Sharma, S. Anand, and S. K. Kaul, "Intelligent Querying for Target Tracking in Camera Networks using Deep Q-Learning with n-Step Bootstrapping", Image and Vision Computing,Vol. 103, 104022, 2020
• A. Jain, P. Goel, S. Aggarwal, A. Fell and S. Anand, "Symmetric k-means for Deep Neural Network Compression and Hardware Acceleration on FPGAs", IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2020,vol. 14, pp. 737-749, DOI: 10.1109/JSTSP.2020.2968810
• S. Anand , S. Mittal, O. Tuzel, P. Meer, "Semi-Supervised Kernel Mean Shift Clustering", IEEE TPAMI, 2014, vol. 36, pp. 1201-1215, DOI: 10.1109/TPAMI.2013.190. code
• S. Mittal, S. Anand , P. Meer, "Generalized Projection Based M-Estimator", IEEE TPAMI, 2012, vol. 34, pp. 2351-2364, DOI: 10.1109/TPAMI.2012.52. code

Selected Refereed Conferences

• D. Sani, A. Iyer, P. Rai, S. Anand, A. Srivastava and K. Kalyanaraman, "Sensor Agnostic Graph-Aware Kalman Filters for Multi-Modal Multi-Object Tracking", to appear, International Conference on Pattern Recognition (ICPR), 2024, (Code - Coming Soon!).
• A. Jindal, V. Goyal, S. Anand and C. Arora, "Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selection", in IEEE WACV 2024. (Code)
• D. Sani, S. Mahato, S. Saini, H. Agarwal, C. Devshali, S. Anand, G. Arora, and T. Jayaraman, "SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated with Key Cropping Parameters", IEEE WACV 2024 (Oral), (Code, Dataset).
• Kshitiz, S. Shreshtha, R. Mounir, M. Vatsa, R. Singh, S. Anand S. Sarkar, and S. M. Parihar, "Long-term Monitoring of Bird Flocks in the Wild", IJCAI 2023, Special Track on AI for Good - Projects.
• S. Agarwal, S. Anand and C. Arora, "Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift", WACV 2023. (Code)
• A. Garg, D. Sani, and S. Anand, "Learning Hierarchy Aware Features for Reducing Mistake Severity", ECCV 2022. (ArXiv Pre-print, Code)
• A. Garg, S. Bagga, Y. Singh, and S. Anand, "HIERMATCH: Leveraging Label Hierarchies for Improving Semi-Supervised Learning", WACV 2022. (Code)
• L. Tiwari, A. Madan, S. Anand and S. Banerjee, "REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions", WACV 2022. (Code)
• A. Sharma, S. Anand and S. K. Kaul, "Intelligent Camera Selection Decisions for Target Tracking in a Camera Network", WACV 2022. (Code)
• S. Agarwal, S. Muku, S. Anand and C. Arora, "Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias", WACV 2022.(Code)
• S. Agarwal, H. Arora, S. Anand, C. Arora, "Contextual Diversity for Active Learning", ECCV 2020. (ArXiv Preprint, Code)
• L. Tiwari, P. Ji, Q. Tran, B. Zhuang, S. Anand, M. Chandraker, "Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction", ECCV 2020. (ArXiv Pre-print).
• E. Bondi, R. Jain, P. Aggrawal, S. Anand, R. Hannaford, A. Kapoor, J. Piavis, S. Shah, L. Joppa, B. Dilkina and M. Tambe, "BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos", WACV 2020.
• A. Shukla, S. Uppal, S. Bhagat, S. Anand and P. Turaga, "PrOSe: Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning", BMVC 2019, (ArXiv Preprint)
• A. Shukla, G. S. Cheema S. Anand, Q. N. Qureshi, and Y. V. Jhala, "Primate Face Identification in the Wild", Pacific-Rim International Conference on Artificial Intelligence, 2019, (ArXiv Preprint)
• A. Sharma, S. Anand and S. K. Kaul, "Reinforcement Learning Based Querying in Camera Networks for Efficient Target Tracking",International Conference on Automated Planning and Scheduling (ICAPS), 2019
• A. Shukla, S. Uppal, S. Bhagat, S. Anand and P. Turaga, "Geometry of Deep Generative Models for Disentangled Representations", ICVGIP 2018, ArXiv pre-print
• A. H. Jha, S. Anand, M. Singh and V. S. R. Veeravasarapu, "Disentangling Factors of Variation with Cycle-Consistent Variational AutoEncoders", ECCV 2018
• M. K. Pal, R. Bhati, A. Sharma, S. K. Kaul, S. Anand and Sujit P. B, "A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving", ITSC 2018
• A. Tripathi, A. Mohan, S. Anand and M. Singh, "Adversarial Learning of Raw Speech Features for Domain Invariant Speech Recognition", ICASSP 2018, pp. 5959-5963, DOI: 10.1109/ICASSP.2018.8462452
• L. Tiwari and S. Anand , "DGSAC: Density Guided SAmpling and Consensus", WACV 2018, pp. 974-982, DOI: 10.1109/WACV.2018.00112
• G. Cheema and S. Anand, "Automatic Detection and Recognition of Individuals in Patterned Species", ECML PKDD, 2017
• A. Jain, A. Fell and S. Anand, "A Parallel Architecture for High Frame Rate Stereo using Semi-Global Matching", BMVC 2017
• L. Tiwari, S. Anand and S. Mittal, "Robust Multi-Model Fitting using Density and Preference Analysis", ACCV, 2016, pp.308-323, DOI: 10.1007/978-3-319-54190-7_19. code
• L. Tiwari and S. Anand , "Fast Hypothesis Filtering For Multi-Structure Geometric Model Fitting", IEEE ICIP, 2016, pp. 3728-3732, DOI: 10.1109/ICIP.2016.7533056.
• A. Shukla and S. Anand , "Metric Learning Based Automatic Segmentation of Patterned Species", IEEE ICIP, 2016, pp. 3982-3986, DOI: 10.1109/ICIP.2016.7533107.
• S. Mittal, S. Anand and P. Meer, "Generalized Projection based M-Estimator: Theory and Applications", IEEE CVPR, 2011, 2689-2696, DOI: 10.1109/CVPR.2011.5995514.
• S. Anand , D. Madigan, R. Mammone, S. Pathak and F. Roberts, "Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures", in Proc. of ISI-2006, LNCS, vol. 3975, Springer, 2006, DOI: 10.1007/11760146_28.

Workshops and Pre-prints

• A. Shukla, P. Turaga, and S. Anand, "GraCIAS: Grassmannian of Corrupted Images for Adversarial Security", arXiv:2005.02936, May, 2020.
• A. Shukla, C. Anderson, G. S. Cheema, P. Guo, S. Onda, D. Anshumaan, S. Anand and R. Farrell, "A Hybrid Approach for Tiger Re-Identification, ICCV 2019 Workshop on Computer Vision for Wildlife Conservation
• A. Shukla, G. S. Cheema and S. Anand, "Unique Identification of Macaques for Population Monitoring and Control", arXiv:1811.00743, 2018
• A. Shukla, G. S. Cheema and S. Anand, "ClusterNet: Semi-Supervised Clustering using Neural Networks", arXiv:1806.01547, 2018
• S. Sinha, M. Agarwal, M. Vatsa, R. Singh and S. Anand, "Exploring Bias in Primate Face Detection and Recognition", ECCV workshop on Bias Estimation in Face Analytics, 2018
• D. Kimothi, A. Shukla, P. Biyani, S. Anand and J. Hogan, "Metric Learning on Biological Sequence Embeddings",IEEE SPAWC 2017, pages 1-5, DOI: 10.1109/SPAWC.2017.8227769
• A. Shukla and S. Anand, "Distance Metric Learning by Optimization on the Stiefel Manifold", In Workshop on DIFFerential Geometry in Computer Vision (DIFF-CV 2015), pages 7.1-7.10. BMVA Press, DOI: 10.5244/C.29.DIFFCV.7
• C. Podilchuk, A. Patel, A. Harthattu, S. Anand and R. Mammone, "A New Face Recognition Algorithm based on Bijective Mappings", IEEE Workshop on FRGC Experiments, CVPR 2005, DOI: 10.1109/CVPR.2005.564.
• S. Anand, D. Madigan, R. Mammone, S. Pathak, F. Roberts, "Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures", DIMACS TR:2006-05.