activity
20182025
most citedDeep Multi-Center Learning for Face Alignment

21 citations · 32 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Real-IAD Variety: Pushing Industrial Anomaly Detection Dataset to a Modern Era

Wenbing Zhu, Chengjie Wang, Bin-Bin Gao +12

Industrial Anomaly Detection (IAD) is a cornerstone for ensuring operational safety, maintaining product quality, and optimizing manufacturing efficiency. However, the advancement…

cs.CV2025

IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction

Ran Yi, Teng Hu, Zihan Su +2

Autoregressive models have emerged as a powerful paradigm for visual content creation, but often overlook the intrinsic structural properties of visual data. Our prior work, IAR, i…

cs.CV2024★ 9 cited

Rethinking Impersonation and Dodging Attacks on Face Recognition Systems

Fengfan Zhou, Qianyu Zhou, Bangjie Yin +4

Face Recognition (FR) systems can be easily deceived by adversarial examples that manipulate benign face images through imperceptible perturbations. Adversarial attacks on FR encom…

cs.CV2018★ 21 cited

Deep Multi-Center Learning for Face Alignment

Zhiwen Shao, Hengliang Zhu, Xin Tan +2

Facial landmarks are highly correlated with each other since a certain landmark can be estimated by its neighboring landmarks. Most of the existing deep learning methods only use o…

cs.GR2018★ 2 cited

Light Transport Simulation via Generalized Multiple Importance Sampling

Qi Liu, Yiheng Zhang, Lizhuang Ma

Multiple importance sampling (MIS) is employed to reduce variance of estimators, but when sampling and weighting are not suitable to the integrand, the estimators would have extra…