2 citations · 2 across the 5 of their papers we have counts for
5 papers
Robust and Efficient Motion Reasoning for Privacy-Aware Classroom Incident Recognition
Paritosh Parmar, Landy Lan, Hong Yang +2
Can computer vision help make classrooms safer? In this pilot study, we investigate privacy-aware and computationally efficient classroom incident recognition from CCTV-style obser…
ChainReaction: Causal Chain-Guided Reasoning for Modular and Explainable Causal-Why Video Question Answering
Paritosh Parmar, Eric Peh, Basura Fernando
Existing Causal-Why Video Question Answering (VideoQA) models often struggle with higher-order reasoning, relying on opaque, monolithic pipelines that entangle video understanding,…
CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Paritosh Parmar, Eric Peh, Ruirui Chen +4
Causal video question answering (QA) has garnered increasing interest, yet existing datasets often lack depth in causal reasoning. To address this gap, we capitalize on the unique…
Learning to Visually Connect Actions and their Effects
Paritosh Parmar, Eric Peh, Basura Fernando
We introduce the novel concept of visually Connecting Actions and Their Effects (CATE) in video understanding. CATE can have applications in areas like task planning and learning f…
Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment
Paritosh Parmar, Amol Gharat, Helge Rhodin
Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout form naturally requires estimating human…