evaluation metrics 1human-in-the-loop 1information bottleneck 1video summarization 1vision-language models 1
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cs.CV2026
VIBE: Annotation-Free Video-to-Text Information Bottleneck Evaluation for TL;DR
Shenghui Chen, Po-han Li, Sandeep Chinchali +1
The paper introduces VIBE, an annotation-free method that evaluates video-to-text summaries by measuring how well they match visual content and how useful they are for downstream d…
cs.CV2026
VEGAS: Human-Aligned Video Caption Evaluation via Gaze
Shenghui Chen, Po-han Li, Ximeng Sun +5
Vision-language models excel at video captioning, yet typically generate descriptions that fail to capture individual viewers' attention. We propose VEGAS (Video caption Evaluation…
cs.CV2026
ViSIL: Unified Evaluation of Information Loss in Multimodal Video Captioning
Po-han Li, Shenghui Chen, Ufuk Topcu +1
Multimodal video captioning condenses dense footage into a structured format of keyframes and natural language. By creating a cohesive multimodal summary, this approach anchors gen…