6 papers · 1 filter
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…
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…
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…
Learning Robust 3D Representation from CLIP via Dual Denoising
Shuqing Luo, Bowen Qu, Wei Gao
In this paper, we explore a critical yet under-investigated issue: how to learn robust and well-generalized 3D representation from pre-trained vision language models such as CLIP.…
Bringing Textual Prompt to AI-Generated Image Quality Assessment
Bowen Qu, Haohui Li, Wei Gao
AI-Generated Images (AGIs) have inherent multimodal nature. Unlike traditional image quality assessment (IQA) on natural scenarios, AGIs quality assessment (AGIQA) takes the corres…
Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution Gap
Bowen Qu, Xiaoyu Liang, Shangkun Sun +1
The recent advancements in Text-to-Video Artificial Intelligence Generated Content (AIGC) have been remarkable. Compared with traditional videos, the assessment of AIGC videos enco…