2.3k citations · 2.4k across the 15 of their papers we have counts for
15 papers
Only Train Once: Uncertainty-Aware One-Class Learning for Face Authenticity Detection
Qingchao Jiang, Zhenxuan Hou, Zhiying Zhu +3
The rapid evolution of generative paradigms has enabled the creation of highly realistic imagery, which escalates the risks of identity fraud and the dissemination of disinformatio…
Evidence-based Decision Modeling for Synthetic Face Detection with Uncertainty-driven Active Learning
Qingchao Jiang, Zhenxuan Hou, Zhiying Zhu +3
With the rapid development of deep generative models, forged facial images are massively exploited for illegal activities. Although existing synthetic face detection methods have a…
Noise-Adaptive Diffusion Sampling for Inverse Problems Without Task-Specific Tuning
Yingzhi Xia, Setthakorn Tanomkiattikun, Liangli Zhen +1
Diffusion models (DMs) have recently shown remarkable performance on inverse problems (IPs). Optimization-based methods can fast solve IPs using DMs as powerful regularizers, but t…
SURE: Semi-dense Uncertainty-REfined Feature Matching
Sicheng Li, Zaiwang Gu, Jie Zhang +3
Establishing reliable image correspondences is essential for many robotic vision problems. However, existing methods often struggle in challenging scenarios with large viewpoint ch…
Learning Intra-view and Cross-view Geometric Knowledge for Stereo Matching
Rui Gong, Weide Liu, Zaiwang Gu +2
Geometric knowledge has been shown to be beneficial for the stereo matching task. However, prior attempts to integrate geometric insights into stereo matching algorithms have large…
Semantic-Human: Neural Rendering of Humans from Monocular Video with Human Parsing
Jie Zhang, Pengcheng Shi, Zaiwang Gu +2
The neural rendering of humans is a topic of great research significance. However, previous works mostly focus on achieving photorealistic details, neglecting the exploration of hu…