2 citations · 3 across the 3 of their papers we have counts for
5 papers · 1 filter
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition
Ishan Rajendrakumar Dave, Mamshad Nayeem Rizve, Mubarak Shah
Real-life applications of action recognition often require a fine-grained understanding of subtle movements, e.g., in sports analytics, user interactions in AR/VR, and surgical vid…
Sync from the Sea: Retrieving Alignable Videos from Large-Scale Datasets
Ishan Rajendrakumar Dave, Fabian Caba Heilbron, Mubarak Shah +1
Temporal video alignment aims to synchronize the key events like object interactions or action phase transitions in two videos. Such methods could benefit various video editing, pr…
SPAct: Self-supervised Privacy Preservation for Action Recognition
Ishan Rajendrakumar Dave, Chen Chen, Mubarak Shah
Visual private information leakage is an emerging key issue for the fast growing applications of video understanding like activity recognition. Existing approaches for mitigating p…
"Knights": First Place Submission for VIPriors21 Action Recognition Challenge at ICCV 2021
Ishan Dave, Naman Biyani, Brandon Clark +3
This technical report presents our approach "Knights" to solve the action recognition task on a small subset of Kinetics-400 i.e. Kinetics400ViPriors without using any extra-data.…
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur +5
Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, an…