62 citations · 102 across the 6 of their papers we have counts for
6 papers
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition
Xiu-Shen Wei, Xuhao Sun, Yang Shen +3
Simplicity Bias (SB) is a phenomenon that deep neural networks tend to rely favorably on simpler predictive patterns but ignore some complex features when applied to supervised dis…
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers
Mingyu Ding, Xiaochen Lian, Linjie Yang +4
High-resolution representations (HR) are essential for dense prediction tasks such as segmentation, detection, and pose estimation. Learning HR representations is typically ignored…
Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification
Peng Wang, Kai Han, Xiu-Shen Wei +2
Learning discriminative image representations plays a vital role in long-tailed image classification because it can ease the classifier learning in imbalanced cases. Given the prom…
Anisotropic Convolutional Networks for 3D Semantic Scene Completion
Jie Li, Kai Han, Peng Wang +2
As a voxel-wise labeling task, semantic scene completion (SSC) tries to simultaneously infer the occupancy and semantic labels for a scene from a single depth and/or RGB image. The…
Cops-Ref: A new Dataset and Task on Compositional Referring Expression Comprehension
Zhenfang Chen, Peng Wang, Lin Ma +2
Referring expression comprehension (REF) aims at identifying a particular object in a scene by a natural language expression. It requires joint reasoning over the textual and visua…
Multi-Label Image Recognition with Graph Convolutional Networks
Zhao-Min Chen, Xiu-Shen Wei, Peng Wang +1
The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model the labe…