160 citations · 174 across the 19 of their papers we have counts for
6 papers · 1 filter
No More Shortcuts: Realizing the Potential of Temporal Self-Supervision
Ishan Rajendrakumar Dave, Simon Jenni, Mubarak Shah
Self-supervised approaches for video have shown impressive results in video understanding tasks. However, unlike early works that leverage temporal self-supervision, current state-…
Egocentric RGB+Depth Action Recognition in Industry-Like Settings
Jyoti Kini, Sarah Fleischer, Ishan Dave +1
Action recognition from an egocentric viewpoint is a crucial perception task in robotics and enables a wide range of human-robot interactions. While most computer vision approaches…
Ensemble Modeling for Multimodal Visual Action Recognition
Jyoti Kini, Sarah Fleischer, Ishan Dave +1
In this work, we propose an ensemble modeling approach for multimodal action recognition. We independently train individual modality models using a variant of focal loss tailored t…
EventTransAct: A video transformer-based framework for Event-camera based action recognition
Tristan de Blegiers, Ishan Rajendrakumar Dave, Adeel Yousaf +1
Recognizing and comprehending human actions and gestures is a crucial perception requirement for robots to interact with humans and carry out tasks in diverse domains, including se…
TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detection
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Video anomaly detection (VAD) without human monitoring is a complex computer vision task that can have a positive impact on society if implemented successfully. While recent advanc…
TimeBalance: Temporally-Invariant and Temporally-Distinctive Video Representations for Semi-Supervised Action Recognition
Ishan Rajendrakumar Dave, Mamshad Nayeem Rizve, Chen Chen +1
Semi-Supervised Learning can be more beneficial for the video domain compared to images because of its higher annotation cost and dimensionality. Besides, any video understanding t…