1 citations · 1 across the 14 of their papers we have counts for
14 papers
Audio-Driven Adversarial Defense for 3D Talking Face Generation with totally Visual Fidelity Preservation
Rui-Qing Sun, Chen-Hao Cui, Hui-Yang Zhao +3
The rapid development of generative portrait models has raised growing concerns about privacy leakage and identity misuse. In particular, audio-driven 3D talking face generation ca…
MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation
Haitian Li, Yanghao Zhou, Heyan Huang +15
In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-visual alignment. However, th…
Do Protective Perturbations Really Protect Portrait Privacy under Real-world Image Transformations?
Ruiqing Sun, Xingshan Yao, Zhijing Wu +6
Proactive defense methods protect portrait images from unauthorized editing or talking face generation (TFG) by introducing pixel-level protective perturbations, and have attracted…
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…
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…
DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys
Guo-Biao Zhang, Xian-Ling Mao, Ding-Yuan Liu +4
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…
MMWOZ: Building Multimodal Agent for Task-oriented Dialogue
Pu-Hai Yang, Heyan Huang, Heng-Da Xu +3
Task-oriented dialogue systems have garnered significant attention due to their conversational ability to accomplish goals, such as booking airline tickets for users. Traditionally…
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…
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…
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…
SEOE: A Scalable and Reliable Semantic Evaluation Framework for Open Domain Event Detection
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Automatic evaluation for Open Domain Event Detection (ODED) is a highly challenging task, because ODED is characterized by a vast diversity of un-constrained output labels from var…
Distribution-Consistency-Guided Multi-modal Hashing
Jin-Yu Liu, Xian-Ling Mao, Tian-Yi Che +1
Multi-modal hashing methods have gained popularity due to their fast speed and low storage requirements. Among them, the supervised methods demonstrate better performance by utiliz…
A Distributed Collaborative Retrieval Framework Excelling in All Queries and Corpora based on Zero-shot Rank-Oriented Automatic Evaluation
Tian-Yi Che, Xian-Ling Mao, Chun Xu +4
Numerous retrieval models, including sparse, dense and llm-based methods, have demonstrated remarkable performance in predicting the relevance between queries and corpora. However,…
Multi-modal Retrieval Augmented Multi-modal Generation: Datasets, Evaluation Metrics and Strong Baselines
Zi-Ao Ma, Tian Lan, Rong-Cheng Tu +6
We present a systematic investigation of Multi-modal Retrieval Augmented Multi-modal Generation (MRAG), a novel task that enables foundation models to process multi-modal web c…