Welcome to the Visualization and Perception (VP) Lab of the Department of Computer Science and Engineering at the Indian Institute of Technology at Madras, India. It was founded in the year 2004 and is headed by Professor Sukhendu Das.

Research works conducted here involves areas like Visual Perception, Computer Vision: Digital Image Processing and Pattern Recognition, Digital Video Processing, Computer Graphics, Artificial Neural Networks, Computational Science and engineering and Soft Computing.

Use the links from the pull-down menus on the left, to find out more about us and our work.

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Achievements and Research Highlights Our Demos Current Members

Salient Highlights :

Latest→ Avishek Bhattacharjee Memorial Best MS Thesis Award (Deptt. of CS&E, IIT Madras) 2023 for the MS thesis entitled "Object Localization using Weakly Supervised Learning Paradigm" , Ms. Sadbhavana Babar.

Latest→ Biswajit Sain Best MS Thesis Award (Deptt. of CS&E, IIT Madras) 2023 for the MS thesis entitled "Object Localization using Weakly Supervised Learning Paradigm" , Ms. Sadbhavana Babar.

Latest→ Avishek Bhattacharjee Memorial Best MS Thesis Award (Deptt. of CS&E, IIT Madras) 2022 for the MS thesis entitled "Audio-Visual Event Localization in Unconstrained Videos using Deep Learning Techniques" , Ms. Janani Ramaswamy.

Latest→ Biswajit Sain Best MS Thesis Award (Deptt. of CS&E, IIT Madras) 2022 for the MS thesis entitled "Audio-Visual Event Localization in Unconstrained Videos using Deep Learning Techniques" , Ms. Janani Ramaswamy.

Latest→ Biswajit Sain Best MS Thesis Award (Deptt. of CS&E, IIT Madras) 2021 for the MS thesis entitled "Video Frame Prediction using Temporal Coherency based Adversarial Networks" , Mr. Prateep Bhattacharjee (joint winner).

→ Best student paper award for the paper,"See the Sound, Hear the Pixels ", Janani Ramaswamy and Sukhendu Das; Accepted in Winter Conference on Applications of Computer Vision (WACV) [#Citations- 53 (June 2023)][A | h5-index - 62 (2022)], Snowmass Village, Colorado, USA, March 2-5, 2020.

→ Best student paper award for the paper, "Motion-based Occlusion-aware Pixel Graph Network for Video Object Segmentation", Saptakatha Adak and Sukhendu Das; In 26th International Conference on Neural Information Processing (ICONIP), Sydney, Australia, December 12-15, 2019. [Paper]

→ "Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks", Prateep Bhattacharjee and Sukhendu Das, In 31st Conference on Advances in Neural Information Processing Systems (NIPS) [Core Rank-A*, Google Rank - 12, h5-index - 245], Vol. 30, pp. 4271-4280; Long Beach, CA, United States of America, December 4-9, 2017; ISBN: 978-1-5108-6096-4; [ #Citations - 54 (June 2023) ] [Paper] [Results][Code-Link]

→ " Directional Attention based Video Frame Prediction using Graph Convolutional Networks.", Prateep Bhattacharjee and Sukhendu Das, In International Joint Conference on Neural Networks (IJCNN) [A | h5-index - 57 (2022)], Budapest, Hungary, July 14-19, 2019. [Google Scholar][DOI:10.1109/IJCNN.2019.8852090] [ #Citations - 5 (June 2022) ].

→ Best student paper award for the paper, "Large Parallax Image Stitching Using an Edge-Preserving Diffeomorphic Warping Process", Geethu Miriam Jacob and Sukhendu Das, in 16th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS), Poitiers, France, 24-27 September, 2018 [Paper][Certificate]

Latest→ Topmost cited (as on June 2022) papers:
(i) "A Survey of Decision Fusion and Feature Fusion Strategies for Pattern Classification"; Utthara Gosa Mangai, Suranjana Samanta, Sukhendu Das and Pinaki Roy Chowdhury; IETE Technical Review, Vol. 27, No. 4, pp. 293-307, July-August 2010. [ #Citations: 313]
[Google Scholar][DOI:10.4103/0256-4602.64604]
(ii) "Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral; satellite images";S Das, T. T Mirnalinee, K Varghese; IEEE Transactions on Geoscience and Remote sensing 49 (10), 3906-3931; (Impact Factor 5.6); Vol. 49, No. 10, pp. 3906-3931, October 2011. [ #Citations: 238][Google Scholar] [DOI:10.1109/TGRS.2011.2136381]