68 citations · 150 across the 34 of their papers we have counts for
36 papers
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…
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data
Aakash Kumar, Chen Chen, Ajmal Mian +2
3D detection is a critical task that enables machines to identify and locate objects in three-dimensional space. It has a broad range of applications in several fields, including a…
Composed Video Retrieval via Enriched Context and Discriminative Embeddings
Omkar Thawakar, Muzammal Naseer, Rao Muhammad Anwer +4
Composed video retrieval (CoVR) is a challenging problem in computer vision which has recently highlighted the integration of modification text with visual queries for more sophist…
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…
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
Yuning Cui, Syed Waqas Zamir, Salman Khan +3
In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent lim…