1 code implementation • 26 Mar 2024 • Shehreen Azad, Yogesh Singh Rawat
Furthermore, we extensively compare ABNet with existing works in person identification and demonstrate its effectiveness for activity-based biometrics across all five datasets.
1 code implementation • 12 Dec 2023 • Ayush Singh, Aayush J Rana, Akash Kumar, Shruti Vyas, Yogesh Singh Rawat
First, we demonstrate its effectiveness on video action detection where the proposed approach outperforms prior works in semi-supervised and weakly-supervised learning along with several baseline approaches in both UCF101-24 and JHMDB-21.
no code implementations • 20 Sep 2023 • Rahul Ambati, Naveed Akhtar, Ajmal Mian, Yogesh Singh Rawat
Inspired by this, we introduce a novel problem of PRofiling Adversarial aTtacks (PRAT).
no code implementations • ICCV 2023 • Nishant Jain, Harkirat Behl, Yogesh Singh Rawat, Vibhav Vineet
A recent trend in deep learning algorithms has been towards training large scale models, having high parameter count and trained on big dataset.
no code implementations • 9 Jun 2023 • Akash Kumar, Ashlesha Kumar, Vibhav Vineet, Yogesh Singh Rawat
In this work, we first provide a benchmark that enables a comparison of existing approaches on the same ground.
Ranked #3 on Self-Supervised Action Recognition on UCF101
no code implementations • 17 Apr 2022 • Rajat Modi, Aayush Jung Rana, Akash Kumar, Praveen Tirupattur, Shruti Vyas, Yogesh Singh Rawat, Mubarak Shah
Beyond possessing large enough size to feed data hungry machines (eg, transformers), what attributes measure the quality of a dataset?
1 code implementation • CVPR 2022 • Akash Kumar, Yogesh Singh Rawat
In this work, we focus on semi-supervised learning for video action detection which utilizes both labeled as well as unlabeled data.
no code implementations • 23 Apr 2020 • Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur, Aayush Jung Rana, Kevin Duarte, Ishan Dave, Yogesh Singh Rawat, Mubarak Shah
For tubelet extraction, we propose a localization network which takes a video clip as input and spatio-temporally detects potential foreground regions at multiple scales to generate action tubelets.