4 citations · 9 across the 7 of their papers we have counts for
5 papers · 1 filter
One Identity, Many Roles: Multimodal Entity Coreference for Enhanced Video Situation Recognition
Balaji Darur, Amanmeet Garg, Makarand Tapaswi
Video Situation Recognition (VidSitu) addresses the challenging problem of "who did what to whom, with what, how, and where" in a video. It tests thorough video understanding by re…
Perceptio: Perception Enhanced Vision Language Models via Spatial Token Generation
Yuchen Li, Amanmeet Garg, Shalini Chaudhuri +2
Large Vision Language Models (LVLMs) excel at semantic understanding but struggle with fine grained spatial grounding, as the model must implicitly infer complex geometry without e…
CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models
Tobia Poppi, Burak Uzkent, Amanmeet Garg +7
Video-language models (VLMs) achieve strong multimodal understanding but remain prone to hallucinations, especially when reasoning about actions and temporal order. Existing mitiga…
Augment the Pairs: Semantics-Preserving Image-Caption Pair Augmentation for Grounding-Based Vision and Language Models
Jingru Yi, Burak Uzkent, Oana Ignat +4
Grounding-based vision and language models have been successfully applied to low-level vision tasks, aiming to precisely locate objects referred in captions. The effectiveness of g…
Audio-Enhanced Text-to-Video Retrieval using Text-Conditioned Feature Alignment
Sarah Ibrahimi, Xiaohang Sun, Pichao Wang +3
Text-to-video retrieval systems have recently made significant progress by utilizing pre-trained models trained on large-scale image-text pairs. However, most of the latest methods…