240 citations
- Megvii (China)14 papers
- Peking UniversityCN4 papers
- Huazhong University of Science and TechnologyCN3 papers
- Institute of Computing TechnologyCN3 papers
- Tsinghua UniversityCN3 papers
- MEI Research (United States)US2 papers
- University of Electronic Science and Technology of ChinaCN2 papers
- Australian National UniversityAU1 paper
- Beijing Institute of TechnologyCN1 paper
- Beijing University of Posts and TelecommunicationsCN1 paper
- Carnegie Mellon UniversityUS1 paper
- Chinese Academy of SciencesCN1 paper
8 papers · 1 filter
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
Shen Cheng, Yuzhi Wang, Haibin Huang +3
In this paper, we introduce NBNet, a novel framework for image denoising. Unlike previous works, we propose to tackle this challenging problem from a new perspective: noise reducti…
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection
Tiancai Wang, Tong Yang, Jiale Cao +1
Object detectors usually achieve promising results with the supervision of complete instance annotations. However, their performance is far from satisfactory with sparse instance a…
EqCo: Equivalent Rules for Self-supervised Contrastive Learning
Benjin Zhu, Junqiang Huang, Zeming Li +2
In this paper, we propose EqCo (Equivalent Rules for Contrastive Learning) to make self-supervised learning irrelevant to the number of negative samples in the contrastive learning…
WeightNet: Revisiting the Design Space of Weight Networks
Ningning Ma, Xiangyu Zhang, Jiawei Huang +1
We present a conceptually simple, flexible and effective framework for weight generating networks. Our approach is general that unifies two current distinct and extremely effective…
CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions
Zhongdao Wang, Jingwei Zhang, Liang Zheng +4
This paper proposes a self-supervised learning method for the person re-identification (re-ID) problem, where existing unsupervised methods usually rely on pseudo labels, such as t…
Attentive Normalization for Conditional Image Generation
Yi Wang, Ying-Cong Chen, Xiangyu Zhang +2
Traditional convolution-based generative adversarial networks synthesize images based on hierarchical local operations, where long-range dependency relation is implicitly modeled w…