102 citations · 191 across the 12 of their papers we have counts for
8 papers · 1 filter
Sculpting Margin Penalty: Intra-Task Adapter Merging and Classifier Calibration for Few-Shot Class-Incremental Learning
Liang Bai, Hong Song, Jinfu Li +6
Real-world applications often face data privacy constraints and high acquisition costs, making the assumption of sufficient training data in incremental tasks unrealistic and leadi…
GMOR: A Lightweight Robust Point Cloud Registration Framework via Geometric Maximum Overlapping
Zhao Zheng, Jingfan Fan, Long Shao +6
Point cloud registration based on correspondences computes the rigid transformation that maximizes the number of inliers constrained within the noise threshold. Current state-of-th…
Efficient Non-Exemplar Class-Incremental Learning with Retrospective Feature Synthesis
Liang Bai, Hong Song, Yucong Lin +5
Despite the outstanding performance in many individual tasks, deep neural networks suffer from catastrophic forgetting when learning from continuous data streams in real-world scen…
Double-Shot 3D Shape Measurement with a Dual-Branch Network for Structured Light Projection Profilometry
Mingyang Lei, Jingfan Fan, Long Shao +6
The structured light (SL)-based three-dimensional (3D) measurement techniques with deep learning have been widely studied to improve measurement efficiency, among which fringe proj…
Mis-classified Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shifeng Zhang, Shuo Wang +3
Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discri…
Learning Meta Model for Zero- and Few-shot Face Anti-spoofing
Yunxiao Qin, Chenxu Zhao, Xiangyu Zhu +6
Face anti-spoofing is crucial to the security of face recognition systems. Most previous methods formulate face anti-spoofing as a supervised learning problem to detect various pre…
Improved Selective Refinement Network for Face Detection
Shifeng Zhang, Rui Zhu, Xiaobo Wang +5
As a long-standing problem in computer vision, face detection has attracted much attention in recent decades for its practical applications. With the availability of face detection…
Support Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shuo Wang, Shifeng Zhang +3
Face recognition has witnessed significant progresses due to the advances of deep convolutional neural networks (CNNs), the central challenge of which, is feature discrimination. T…