961 citations
- Nankai UniversityCN47 papers
- Chinese Academy of SciencesCN23 papers
- Tsinghua UniversityCN21 papers
- Nanyang Technological UniversitySG16 papers
- University of Science and Technology of ChinaCN14 papers
- Centre National de la Recherche ScientifiqueFR13 papers
- Hong Kong Polytechnic UniversityHK11 papers
- Peking UniversityCN10 papers
- City University of Hong KongHK9 papers
- Harbin Institute of TechnologyCN9 papers
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78 papers · 1 filter
AM-Net: Adaptively Aligned Multi-Scale Moment for Few-Shot Action Recognition
Zilin Gao, Qilong Wang, Bingbing Zhang +2
Thanks to capability to alleviate the cost of large-scale annotation, few-shot action recognition (FSAR) has attracted increased attention of researchers in recent years. Existing…
Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation
Qiangguo Jin, Hui Cui, Junbo Wang +7
Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-l…
NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation
Xuzhi Wang, Wei Feng, Lingdong Kong +1
LiDAR semantic segmentation plays a vital role in autonomous driving. Existing voxel-based methods for LiDAR semantic segmentation apply uniform partition to the 3D LiDAR point clo…
Differential Alignment for Domain Adaptive Object Detection
Xinyu He, Xinhui Li, Xiaojie Guo
Domain adaptive object detection (DAOD) aims to generalize an object detector trained on labeled source-domain data to a target domain without annotations, the core principle of wh…
Multi-Level Correlation Network For Few-Shot Image Classification
Yunkai Dang, Min Zhang, Zhengyu Chen +4
Few-shot image classification(FSIC) aims to recognize novel classes given few labeled images from base classes. Recent works have achieved promising classification performance, esp…
Dynamic Brightness Adaptation for Robust Multi-modal Image Fusion
Yiming Sun, Bing Cao, Pengfei Zhu +1
Infrared and visible image fusion aim to integrate modality strengths for visually enhanced, informative images. Visible imaging in real-world scenarios is susceptible to dynamic e…