160 citations · 162 across the 14 of their papers we have counts for
6 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…
GAReT: Cross-view Video Geolocalization with Adapters and Auto-Regressive Transformers
Manu S Pillai, Mamshad Nayeem Rizve, Mubarak Shah
Cross-view video geo-localization (CVGL) aims to derive GPS trajectories from street-view videos by aligning them with aerial-view images. Despite their promising performance, curr…
Open Vocabulary Multi-Label Video Classification
Rohit Gupta, Mamshad Nayeem Rizve, Jayakrishnan Unnikrishnan +5
Pre-trained vision-language models (VLMs) have enabled significant progress in open vocabulary computer vision tasks such as image classification, object detection and image segmen…
VidLA: Video-Language Alignment at Scale
Mamshad Nayeem Rizve, Fan Fei, Jayakrishnan Unnikrishnan +5
In this paper, we propose VidLA, an approach for video-language alignment at scale. There are two major limitations of previous video-language alignment approaches. First, they do…
CodaMal: Contrastive Domain Adaptation for Malaria Detection in Low-Cost Microscopes
Ishan Rajendrakumar Dave, Tristan de Blegiers, Chen Chen +1
Malaria is a major health issue worldwide, and its diagnosis requires scalable solutions that can work effectively with low-cost microscopes (LCM). Deep learning-based methods have…