1 code implementation • 13 Nov 2024 • Sanjay Haresh, Daniel Dijkman, Apratim Bhattacharyya, Roland Memisevic
Robotics tasks are highly compositional by nature.
2 code implementations • CVPR 2024 • Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Triantafyllos Afouras, Kumar Ashutosh, Vijay Baiyya, Siddhant Bansal, Bikram Boote, Eugene Byrne, Zach Chavis, Joya Chen, Feng Cheng, Fu-Jen Chu, Sean Crane, Avijit Dasgupta, Jing Dong, Maria Escobar, Cristhian Forigua, Abrham Gebreselasie, Sanjay Haresh, Jing Huang, Md Mohaiminul Islam, Suyog Jain, Rawal Khirodkar, Devansh Kukreja, Kevin J Liang, Jia-Wei Liu, Sagnik Majumder, Yongsen Mao, Miguel Martin, Effrosyni Mavroudi, Tushar Nagarajan, Francesco Ragusa, Santhosh Kumar Ramakrishnan, Luigi Seminara, Arjun Somayazulu, Yale Song, Shan Su, Zihui Xue, Edward Zhang, Jinxu Zhang, Angela Castillo, Changan Chen, Xinzhu Fu, Ryosuke Furuta, Cristina Gonzalez, Prince Gupta, Jiabo Hu, Yifei HUANG, Yiming Huang, Weslie Khoo, Anush Kumar, Robert Kuo, Sach Lakhavani, Miao Liu, Mi Luo, Zhengyi Luo, Brighid Meredith, Austin Miller, Oluwatumininu Oguntola, Xiaqing Pan, Penny Peng, Shraman Pramanick, Merey Ramazanova, Fiona Ryan, Wei Shan, Kiran Somasundaram, Chenan Song, Audrey Southerland, Masatoshi Tateno, Huiyu Wang, Yuchen Wang, Takuma Yagi, Mingfei Yan, Xitong Yang, Zecheng Yu, Shengxin Cindy Zha, Chen Zhao, Ziwei Zhao, Zhifan Zhu, Jeff Zhuo, Pablo Arbelaez, Gedas Bertasius, David Crandall, Dima Damen, Jakob Engel, Giovanni Maria Farinella, Antonino Furnari, Bernard Ghanem, Judy Hoffman, C. V. Jawahar, Richard Newcombe, Hyun Soo Park, James M. Rehg, Yoichi Sato, Manolis Savva, Jianbo Shi, Mike Zheng Shou, Michael Wray
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge.
no code implementations • CVPR 2024 • Mukul Khanna, Yongsen Mao, Hanxiao Jiang, Sanjay Haresh, Brennan Shacklett, Dhruv Batra, Alexander Clegg, Eric Undersander, Angel X. Chang, Manolis Savva
Surprisingly, we observe that agents trained on just 122 scenes from our dataset outperform agents trained on 10, 000 scenes from the ProcTHOR-10K dataset in terms of zero-shot generalization in real-world scanned environments.
1 code implementation • 12 Sep 2022 • Sanjay Haresh, Xiaohao Sun, Hanxiao Jiang, Angel X. Chang, Manolis Savva
Human-object interactions with articulated objects are common in everyday life.
no code implementations • 30 Jun 2022 • Hamza Khan, Sanjay Haresh, Awais Ahmed, Shakeeb Siddiqui, Andrey Konin, M. Zeeshan Zia, Quoc-Huy Tran
We introduce a novel approach for temporal activity segmentation with timestamp supervision.
1 code implementation • CVPR 2022 • Sateesh Kumar, Sanjay Haresh, Awais Ahmed, Andrey Konin, M. Zeeshan Zia, Quoc-Huy Tran
The temporal optimal transport module enables our approach to learn effective representations for unsupervised activity segmentation.
Ranked #1 on
Unsupervised Action Segmentation
on 50 Salads
no code implementations • CVPR 2021 • Sanjay Haresh, Sateesh Kumar, Huseyin Coskun, Shahram Najam Syed, Andrey Konin, Muhammad Zeeshan Zia, Quoc-Huy Tran
To overcome this problem, we propose a temporal regularization term (i. e., Contrastive-IDM) which encourages different frames to be mapped to different points in the embedding space.
no code implementations • 11 Apr 2020 • Sanjay Haresh, Sateesh Kumar, M. Zeeshan Zia, Quoc-Huy Tran
We apply: (i) one-class classification loss and (ii) reconstruction-based loss, for anomaly detection on RetroTrucks as well as on existing static-camera datasets.