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cs.CV2025
Enhancing Long Video Question Answering with Scene-Localized Frame Grouping
Xuyi Yang, Wenhao Zhang, Hongbo Jin +5
Current Multimodal Large Language Models (MLLMs) often perform poorly in long video understanding, primarily due to resource limitations that prevent them from processing all video…
cs.CV2025
TAR: Temporal Anchor-Constrained Reasoning for Video Temporal Grounding
Chaohong Guo, Xun Mo, Yongwei Nie +3
Video Temporal Grounding (VTG) aims to localize specific video segments corresponding to natural language queries. While recent Large Vision-Language Models (LVLMs) employ Reinforc…
cs.AI2025
Invert4TVG: A Temporal Video Grounding Framework with Inversion Tasks Preserving Action Understanding Ability
Zhaoyu Chen, Hongnan Lin, Yongwei Nie +4
Temporal Video Grounding (TVG) aims to localize video segments corresponding to a given textual query, which often describes human actions. However, we observe that current methods…