2 citations · 3 across the 15 of their papers we have counts for
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cs.CV2026
VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing
Andong Deng, Dawei Du, Zhenfang Chen +7
Real-world video editing demands not only expert knowledge of cinematic techniques but also multimodal reasoning to select, align, and combine footage into coherent narratives. Whi…
cs.CV2026
Granular Ball Guided Stable Latent Domain Discovery for Domain-General Crowd Counting
Fan Chen, Shuyin Xia, Yi Wang
Single-source domain generalization for crowd counting is highly challenging because a single labeled source domain may contain heterogeneous latent domains, while unseen target do…
cs.CV2026
SAMA: Factorized Semantic Anchoring and Motion Alignment for Instruction-Guided Video Editing
Xinyao Zhang, Wenkai Dong, Yuxin Song +10
Current instruction-guided video editing models struggle to simultaneously balance precise semantic modifications with faithful motion preservation. While existing approaches rely…