3 papers
cs.CV2026
Grounding Confusable Movie Moments
Dong-Hee Kim, Seonwoo Choi, Changbeen Kim +5
Characters, locations, and actions recur throughout a movie, so many of its moments differ only in fine-grained details. Grounding such a moment in a full-length movie requires res…
cs.CV2026
VidOmni-Bench: A Benchmark for Fine-Grained Video Understanding via Spatio-Temporal Event Verification across Complexity and Duration
Changbeen Kim, Junwon Chang, Kipyo Kim +3
While Video Large Language Models (Video-LLMs) have recently demonstrated strong performance, reliably evaluating their fine-grained video understanding remains challenging. Existi…
cs.CV2026
Beyond Visual Boundaries: Rethinking Scene Segmentation for Movie RAG
Dong-Hee Kim, Seonwoo Choi, Changbeen Kim +6
Understanding long-form video remains a fundamental challenge for multimodal large language models (MLLMs). Sparse frame sampling fails to capture fine-grained visual details, whil…