1.6k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Vi Technology (United States)US14 papers
- Tsinghua UniversityCN12 papers
- Peking UniversityCN10 papers
- University of Electronic Science and Technology of ChinaCN10 papers
- Chinese Academy of SciencesCN9 papers
- Huazhong University of Science and TechnologyCN8 papers
- Hong Kong University of Science and TechnologyHK7 papers
- Tongji UniversityCN5 papers
- University of Science and Technology of ChinaCN5 papers
- Chinese University of Hong KongHK4 papers
- Institute of AutomationCN4 papers
- Tencent (China)CN4 papers
77 papers · 1 filter
Class Balance Matters to Active Class-Incremental Learning
Zitong Huang, Ze Chen, Yuanze Li +6
Few-Shot Class-Incremental Learning has shown remarkable efficacy in efficient learning new concepts with limited annotations. Nevertheless, the heuristic few-shot annotations may…
PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training
Suyi Chen, Hao Xu, Haipeng Li +5
Data plays a crucial role in training learning-based methods for 3D point cloud registration. However, the real-world dataset is expensive to build, while rendering-based synthetic…
Label-guided Attention Distillation for Lane Segmentation
Zhikang Liu, Lanyun Zhu
Contemporary segmentation methods are usually based on deep fully convolutional networks (FCNs). However, the layer-by-layer convolutions with a growing receptive field is not good…
Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling
Hansen Feng, Lizhi Wang, Yuzhi Wang +1
Low-light raw denoising is an important and valuable task in computational photography where learning-based methods trained with paired real data are mainstream. However, the limit…
SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation
Yaochen Li, Yuhui Hong, Yonghong Song +3
Video object segmentation (VOS) is an essential part of autonomous vehicle navigation. The real-time speed is very important for the autonomous vehicle algorithms along with the ac…
Temporal Knowledge Consistency for Unsupervised Visual Representation Learning
Weixin Feng, Yuanjiang Wang, Lihua Ma +2
The instance discrimination paradigm has become dominant in unsupervised learning. It always adopts a teacher-student framework, in which the teacher provides embedded knowledge as…
GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning
Haipeng Li, Kunming Luo, Shuaicheng Liu
Existing optical flow methods are erroneous in challenging scenes, such as fog, rain, and night because the basic optical flow assumptions such as brightness and gradient constancy…
DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
Haipeng Li, Shuaicheng Liu, Jue Wang
Mobile captured images can be aligned using their gyroscope sensors. Optical image stabilizer (OIS) terminates this possibility by adjusting the images during the capturing. In thi…
JigsawGAN: Auxiliary Learning for Solving Jigsaw Puzzles with Generative Adversarial Networks
Ru Li, Shuaicheng Liu, Guangfu Wang +2
The paper proposes a solution based on Generative Adversarial Network (GAN) for solving jigsaw puzzles. The problem assumes that an image is divided into equal square pieces, and a…
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…
TP-LSD: Tri-Points Based Line Segment Detector
Siyu Huang, Fangbo Qin, Pengfei Xiong +3
This paper proposes a novel deep convolutional model, Tri-Points Based Line Segment Detector (TP-LSD), to detect line segments in an image at real-time speed. The previous related…
LabelEnc: A New Intermediate Supervision Method for Object Detection
Miao Hao, Yitao Liu, Xiangyu Zhang +1
In this paper we propose a new intermediate supervision method, named LabelEnc, to boost the training of object detection systems. The key idea is to introduce a novel label encodi…
Spherical Feature Transform for Deep Metric Learning
Yuke Zhu, Yan Bai, Yichen Wei
Data augmentation in feature space is effective to increase data diversity. Previous methods assume that different classes have the same covariance in their feature distributions.…
Prime-Aware Adaptive Distillation
Youcai Zhang, Zhonghao Lan, Yuchen Dai +4
Knowledge distillation(KD) aims to improve the performance of a student network by mimicing the knowledge from a powerful teacher network. Existing methods focus on studying what k…
Hierarchical Context Embedding for Region-based Object Detection
Zhao-Min Chen, Xin Jin, Borui Zhao +2
State-of-the-art two-stage object detectors apply a classifier to a sparse set of object proposals, relying on region-wise features extracted by RoIPool or RoIAlign as inputs. The…
Funnel Activation for Visual Recognition
Ningning Ma, Xiangyu Zhang, Jian Sun
We present a conceptually simple but effective funnel activation for image recognition tasks, called Funnel activation (FReLU), that extends ReLU and PReLU to a 2D activation by ad…
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…
BorderDet: Border Feature for Dense Object Detection
Han Qiu, Yuchen Ma, Zeming Li +2
Dense object detectors rely on the sliding-window paradigm that predicts the object over a regular grid of image. Meanwhile, the feature maps on the point of the grid are adopted t…
Weight-dependent Gates for Network Pruning
Yun Li, Zechun Liu, Weiqun Wu +4
In this paper, a simple yet effective network pruning framework is proposed to simultaneously address the problems of pruning indicator, pruning ratio, and efficiency constraint. T…
3DV: 3D Dynamic Voxel for Action Recognition in Depth Video
Yancheng Wang, Yang Xiao, Fu Xiong +4
To facilitate depth-based 3D action recognition, 3D dynamic voxel (3DV) is proposed as a novel 3D motion representation. With 3D space voxelization, the key idea of 3DV is to encod…
Joint Multi-Dimension Pruning via Numerical Gradient Update
Zechun Liu, Xiangyu Zhang, Zhiqiang Shen +4
We present joint multi-dimension pruning (abbreviated as JointPruning), an effective method of pruning a network on three crucial aspects: spatial, depth and channel simultaneously…