2 papers
cs.CV2024
Exploiting Minority Pseudo-Labels for Semi-Supervised Fine-grained Road Scene Understanding
Yuting Hong, Yongkang Wu, Hui Xiao +4
In fine-grained road scene understanding, semantic segmentation plays a crucial role in enabling vehicles to perceive and comprehend their surroundings. By assigning a specific cla…
cs.CV2023
Semi-Supervised Learning with Pseudo-Negative Labels for Image Classification
Hao Xu, Hui Xiao, Huazheng Hao +3
Semi-supervised learning frameworks usually adopt mutual learning approaches with multiple submodels to learn from different perspectives. To avoid transferring erroneous pseudo la…