most citedT2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation

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cs.CV2025

Your Vision-Language Model Can't Even Count to 20: Exposing the Failures of VLMs in Compositional Counting

Xuyang Guo, Zekai Huang, Zhenmei Shi +2

Vision-Language Models (VLMs) have become a central focus of today's AI community, owing to their impressive abilities gained from training on large-scale vision-language data from…

cs.CV2025

T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation

Yubin Chen, Xuyang Guo, Zhenmei Shi +2

Text-to-video (T2V) models have shown remarkable performance in generating visually reasonable scenes, while their capability to leverage world knowledge for ensuring semantic cons…

cs.CV2025

T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models

Xuyang Guo, Jiayan Huo, Zhenmei Shi +3

Thanks to recent advancements in scalable deep architectures and large-scale pretraining, text-to-video generation has achieved unprecedented capabilities in producing high-fidelit…