2 citations · 5 across the 22 of their papers we have counts for
14 papers · 1 filter
CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation
Yunhe Li, Likun Wu, Sijing Wu +5
Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-defined camera trajectories. Howev…
PCQA-R1: Advancing Generalized 3D Point Cloud Quality Assessment with Reinforcement Learning
Kangning Ye, Yunhao Li, Sijing Wu +2
No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of point clouds. However, larg…
FMReward: Aligning and Evaluating Audio-Driven 3D Facial Animation with Human Preferences
Sijing Wu, Yunhao Li, Zhilin Gao +4
Audio-driven 3D facial animation is essential for advancing immersion and interactivity in virtual experiences. Although recent advances have shown promising capabilities, the trai…
Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model
Sijing Wu, Yunhao Li, Huiyu Duan +4
AI-generated human-centric videos play a crucial role in a wide range of modern applications. However, they often suffer from quality issues and semantic mismatches, underscoring t…
VideoAesBench: Benchmarking the Video Aesthetics Perception Capabilities of Large Multimodal Models
Yunhao Li, Sijing Wu, Zhilin Gao +5
Large multimodal models (LMMs) have demonstrated outstanding capabilities in various visual perception tasks, which has in turn made the evaluation of LMMs significant. However, th…
Q-Bench-Portrait: Benchmarking Multimodal Large Language Models on Portrait Image Quality Perception
Sijing Wu, Yunhao Li, Zicheng Zhang +5
Recent advances in multimodal large language models (MLLMs) have demonstrated impressive performance on existing low-level vision benchmarks, which primarily focus on generic image…