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cs.CV2026

Structured Hyperedge Adaptation for Parameter-Efficient Fine-Tuning of Vision Transformers

Edwin Kwadwo Tenagyei, Lei Wang, Ugochukwu Ejike Akpudo +2

Parameter-efficient fine-tuning (PEFT) has become a practical solution for adapting large pretrained vision transformers (ViTs) to downstream tasks while updating only a small subs…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

Guided Path Sampling: Steering Diffusion Models Back on Track with Principled Path Guidance

Haosen Li, Wenshuo Chen, Shaofeng Liang +3

Iterative refinement methods based on a denoising-inversion cycle are powerful tools for enhancing the quality and control of diffusion models. However, their effectiveness is crit…