most citedContent-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware Consistency

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

IE-Critic-R1: Advancing the Explanatory Measurement of Text-Driven Image Editing for Human Perception Alignment

Bowen Qu, Shangkun Sun, Xiaoyu Liang +1

Recent advances in text-driven image editing have been significant, yet the task of accurately evaluating these edited images continues to pose a considerable challenge. Different…

cs.CV2025

Flow4Agent: Long-form Video Understanding via Motion Prior from Optical Flow

Ruyang Liu, Shangkun Sun, Haoran Tang +2

Long-form video understanding has always been a challenging problem due to the significant redundancy in both temporal and spatial contents. This challenge is further exacerbated b…

cs.CV2025

VideoGen-Eval: Agent-based System for Video Generation Evaluation

Yuhang Yang, Ke Fan, Shangkun Sun +7

The rapid advancement of video generation has rendered existing evaluation systems inadequate for assessing state-of-the-art models, primarily due to simple prompts that cannot sho…

cs.CV20251 cited

Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware Consistency

Shangkun Sun, Xiaoyu Liang, Bowen Qu +1

The advent of next-generation video generation models like \textit{Sora} poses challenges for AI-generated content (AIGC) video quality assessment (VQA). These models substantially…

cs.CV2025

IE-Bench: Advancing the Measurement of Text-Driven Image Editing for Human Perception Alignment

Shangkun Sun, Bowen Qu, Xiaoyu Liang +2

Recent advances in text-driven image editing have been significant, yet the task of accurately evaluating these edited images continues to pose a considerable challenge. Different…