activity
20242026
collaborators

12 papers

cs.MM2026

MTAVG-Bench: A Diagnostic Benchmark for Multi-Talker Dialogue-Centric Audio-Video Generation

Yang-Hao Zhou, Haitian Li, Rexar Lin +12

Recent advances in text-to-audio-video (T2AV) generation have enabled models to synthesize audio-visual videos with multi-participant dialogues. However, existing evaluation benchm…

cs.CV2026

ISExplore:Informative Segment Selection for Efficient Personalized 3D Talking Face Generation

Rui-Qing Sun, Ang Li, Zhijing Wu +5

Talking Face Generation (TFG) methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have recently achieved impressive progress in personalized talking hea…

cs.AI2026

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys

Guo-Biao Zhang, Ding-Yuan Liu, Da-Yi Wu +5

The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to evaluate the quality of generated surve…

cs.CV2026

Efficient and Robust Video Defense Framework against 3D-field Personalized Talking Face

Rui-qing Sun, Xingshan Yao, Tian Lan +6

State-of-the-art 3D-field video-referenced Talking Face Generation (TFG) methods synthesize high-fidelity personalized talking-face videos in real time by modeling 3D geometry and…

cs.CL2025

A Survey of Automatic Evaluation Methods on Text, Visual and Speech Generations

Tian Lan, Yang-Hao Zhou, Zi-Ao Ma +8

Recent advances in deep learning have significantly enhanced generative AI capabilities across text, images, and audio. However, automatically evaluating the quality of these gener…

cs.AI2025

T2I-Eval-R1: Reinforcement Learning-Driven Reasoning for Interpretable Text-to-Image Evaluation

Zi-Ao Ma, Tian Lan, Rong-Cheng Tu +5

The rapid progress in diffusion-based text-to-image (T2I) generation has created an urgent need for interpretable automatic evaluation methods that can assess the quality of genera…