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cs.CV2024
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model
Khoa Vo, Thinh Phan, Kashu Yamazaki +2
Current video-language models (VLMs) rely extensively on instance-level alignment between video and language modalities, which presents two major limitations: (1) visual reasoning…
cs.CV2024
-Bench: Benchmarking the Robustness of Referring Perception Models under Perturbations
Xiang Li, Kai Qiu, Jinglu Wang +6
Referring perception, which aims at grounding visual objects with multimodal referring guidance, is essential for bridging the gap between humans, who provide instructions, and the…