activity
20242026
collaborators

6 papers

cs.AI2026

Open Evaluation Agent: Efficient and Promptable Evaluation of Visual Generative Models

Shulin Tian, Ziqi Huang, Fan Zhang +3

Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hundreds or thousands of images…

cs.CV2026

Gloria: Consistent Character Video Generation via Content Anchors

Yuhang Yang, Fan Zhang, Huaijin Pi +5

Digital characters are central to modern media, yet generating character videos with long-duration, consistent multi-view appearance and expressive identity remains challenging. Ex…

cs.CV2025

VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Dian Zheng, Ziqi Huang, Hongbo Liu +9

Video generation has advanced significantly, evolving from producing unrealistic outputs to generating videos that appear visually convincing and temporally coherent. To evaluate t…

cs.CV2025

Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models

Fan Zhang, Shulin Tian, Ziqi Huang +2

Recent advancements in visual generative models have enabled high-quality image and video generation, opening diverse applications. However, evaluating these models often demands s…

cs.CV2025

ShotBench: Expert-Level Cinematic Understanding in Vision-Language Models

Hongbo Liu, Jingwen He, Yi Jin +11

Cinematography, the fundamental visual language of film, is essential for conveying narrative, emotion, and aesthetic quality. While recent Vision-Language Models (VLMs) demonstrat…

cs.CV2024

VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models

Ziqi Huang, Fan Zhang, Xiaojie Xu +14

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable…