I am a first-year PhD student at the University of Bristol working with Prof. Dima Damen. My research interest is Computer Vision, Pattern Recognition, and Machine Learning. Currently, I am working on devising learning-based methods for understanding and exploring various aspects of first-person (egocentric) vision. Previously, at CVIT, IIIT Hyderabad, I worked with Prof. C.V. Jawahar and Prof. Chetan Arora on unsupervised procedure learning from egocentric videos. Earlier, I worked on improving word recognition and retrieval in large document collection with Prof. C.V. Jawahar and on 3D Computer Vision with Prof. Shanmuganathan Raman.
My ultimate goal is to contribute to the development of systems capable of understanding the world as we do. I’m an inquisitive person, and I’m always willing to learn about fields including, but not limited to, science, technology, astrophysics, and physics.
June, 2023 : Co-organising the Joint International 3rd Ego4D and 11th EPIC Workshop @ CVPR 2023.
Feb, 2023 : Successfully defended my master’s thesis, I-Do, You-Learn: Techniques for Unsupervised Procedure Learning using Egocentric Videos.
Nov, 2022 : Gave a talk on Procedure Learning from Egocentric Videos at Computer Vision Centre, Universitat Autònoma de Barcelona, hosted by Prof. Dimosthenis Karatzas.
Nov, 2022 : Co-organised the 2nd International Ego4D Workshop @ ECCV 2022.
Machine Learning and Computer Vision (MaVi) @ University of Bristol
We propose the EgoProceL dataset consisting of 62 hours of videos captured by 130 subjects performing 16 tasks and a self-supervised Correspond and Cut (CnC) framework for procedure learning. CnC utilizes the temporal correspondences between the key-steps across multiple videos to learn the procedure.
European Conference on Computer Vision (ECCV), 2022
We offer 3,670 hours of daily-life activity video spanning hundreds of scenarios captured by 931 unique camera wearers from 74 worldwide locations and 9 different countries.
We present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities).
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Christian Fuegen, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik
Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (ORAL; Best paper finalist [link])
We propose to fuse recognition-based and recognition-free approaches for word recognition using learning-based methods.
International Conference on Pattern Recognition (ICPR), 2020
Fusing recognition-based and recognition-free approaches using rule-based methods for improving word recognition and retrieval.
IAPR International Workshop on Document Analysis and System (DAS), 2020 (ORAL)
Egocentric Videos for Procedure Learning @ Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2022) (Vision India). [slides; tweet; linkedin]
Egocentric Videos for Procedure Learning @ Computer Vision Centre, Universitat Autònoma de Barcelona [slides; tweet]
This paper proposes a Generative Adversarial Network (GAN) based architecture called Deep Future Gaze (DFG) for addressing the task of gaze anticipation in egocentric videos.
This paper proposes a three-stream convolutional neural network architecture for the task of action recognition in first-person videos.
This paper proposes a two-stream convolutional neural network architecture for the task of action recognition in a video.