105 citations · 108 across the 8 of their papers we have counts for
8 papers
Semi-supervised Semantic Segmentation with Multi-Constraint Consistency Learning
Jianjian Yin, Tao Chen, Gensheng Pei +3
Consistency regularization has prevailed in semi-supervised semantic segmentation and achieved promising performance. However, existing methods typically concentrate on enhancing t…
Universal Organizer of SAM for Unsupervised Semantic Segmentation
Tingting Li, Gensheng Pei, Xinhao Cai +3
Unsupervised semantic segmentation (USS) aims to achieve high-quality segmentation without manual pixel-level annotations. Existing USS models provide coarse category classificatio…
VideoMAC: Video Masked Autoencoders Meet ConvNets
Gensheng Pei, Tao Chen, Xiruo Jiang +3
Recently, the advancement of self-supervised learning techniques, like masked autoencoders (MAE), has greatly influenced visual representation learning for images and videos. Never…
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
Huafeng Liu, Mengmeng Sheng, Zeren Sun +3
Learning with noisy labels has gained increasing attention because the inevitable imperfect labels in real-world scenarios can substantially hurt the deep model performance. Recent…
FECANet: Boosting Few-Shot Semantic Segmentation with Feature-Enhanced Context-Aware Network
Huafeng Liu, Pai Peng, Tao Chen +3
Few-shot semantic segmentation is the task of learning to locate each pixel of the novel class in the query image with only a few annotated support images. The current correlation-…
Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Noisy Samples and Utilizing Hard Ones
Huafeng Liu, Chuanyi Zhang, Yazhou Yao +4
Labeling objects at a subordinate level typically requires expert knowledge, which is not always available when using random annotators. As such, learning directly from web images…
Deep Representation Learning for Road Detection through Siamese Network
Huafeng Liu, Xiaofeng Han, Xiangrui Li +3
Robust road detection is a key challenge in safe autonomous driving. Recently, with the rapid development of 3D sensors, more and more researchers are trying to fuse information ac…
Road Segmentation with Image-LiDAR Data Fusion
Huafeng Liu, Yazhou Yao, Zeren Sun +3
Robust road segmentation is a key challenge in self-driving research. Though many image-based methods have been studied and high performances in dataset evaluations have been repor…