10 papers
Temporally-Aligned Evaluation for Audio-Driven Talking Head Generation
Zhicheng Zhang, Lei Wang, Yu Zhang +1
Audio-driven talking-head generation has advanced rapidly, yet existing evaluation protocols mainly rely on frame-wise metrics that assume strict temporal correspondence between ge…
Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation
Zhicheng Zhang, Lei Wang, Yu Zhang +1
Audio-driven talking-head generation has achieved remarkable progress with recent models such as AniTalker, FLOAT, and Sonic. Despite their success, most existing approaches rely o…
Trust-Aware Joint Feature-Prediction Discrepancy for Robust Domain Adaptation
Xi Ding, Lei Wang, Syuan-Hao Li +1
Domain adaptation aims to mitigate performance degradation caused by distribution shifts between a labeled source domain and an unlabeled or sparsely labeled target domain. Most ex…
Uncertainty-DTW for Sequences and Visual Tokens
Lei Wang, Syuan-Hao Li, Yongsheng Gao +1
Aligning structured data is a fundamental problem in computer vision and machine learning, underlying tasks such as time series analysis, human action recognition, and visual repre…
Privacy-Aware Video Anomaly Detection through Orthogonal Subspace Projection
Lei Wang, Wenxiang Diao, Andrew Busch +2
Video anomaly detection (VAD) systems often prioritize accuracy while overlooking privacy concerns, limiting their suitability for real-world deployment. We propose the Orthogonal…
Subspace Kernel Learning on Tensor Sequences
Lei Wang, Xi Ding, Yongsheng Gao +1
Learning from structured multi-way data, represented as higher-order tensors, requires capturing complex interactions across tensor modes while remaining computationally efficient.…
Learning Time in Static Classifiers
Xi Ding, Lei Wang, Piotr Koniusz +1
Real-world visual data rarely presents as isolated, static instances. Instead, it often evolves gradually over time through variations in pose, lighting, object state, or scene con…
Graph Your Own Prompt
Xi Ding, Lei Wang, Piotr Koniusz +1
We propose Graph Consistency Regularization (GCR), a novel framework that injects relational graph structures, derived from model predictions, into the learning process to promote…
Video Understanding by Design: How Datasets Shape Video Models
Lei Wang, Syuan-Hao Li, Piotr Koniusz +1
Research in video understanding has advanced rapidly, driven by increasingly diverse datasets and more powerful model architectures. While existing surveys typically organize progr…
Referring Human Pose and Mask Estimation in the Wild
Bo Miao, Mingtao Feng, Zijie Wu +3
We introduce Referring Human Pose and Mask Estimation (R-HPM) in the wild, where either a text or positional prompt specifies the person of interest in an image. This new task hold…