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cs.CV2025
ViDiC: Video Difference Captioning
Jiangtao Wu, Shihao Li, Zhaozhou Bian +7
Understanding visual differences between dynamic scenes requires the comparative perception of compositional, spatial, and temporal changes--a capability that remains underexplored…
cs.CV2025
IF-VidCap: Can Video Caption Models Follow Instructions?
Shihao Li, Yuanxing Zhang, Jiangtao Wu +20
Although Multimodal Large Language Models (MLLMs) have demonstrated proficiency in video captioning, practical applications require captions that follow specific user instructions…
cs.CV2025
MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues
Yaning Pan, Qianqian Xie, Guohui Zhang +13
The recent development of Multimodal Large Language Models (MLLMs) has significantly advanced AI's ability to understand visual modalities. However, existing evaluation benchmarks…