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- Chinese Academy of SciencesCN17 papers
- Tsinghua UniversityCN17 papers
- Ministry of Industry and Information TechnologyCN16 papers
- Xi'an Jiaotong UniversityCN16 papers
- Xidian UniversityCN16 papers
- Australian National UniversityAU11 papers
- Moscow Institute of Physics and TechnologyRU11 papers
- University of Chinese Academy of SciencesCN10 papers
- Beijing Normal UniversityCN9 papers
- Nankai UniversityCN9 papers
- Centre National de la Recherche ScientifiqueFR8 papers
- Fudan UniversityCN8 papers
7 papers · 2 filters
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
Yang Wang, Bo Dong, Ke Xu +4
Deep Neural Networks (DNNs) are widely used for computer vision tasks. However, it has been shown that deep models are vulnerable to adversarial attacks, i.e., their performances d…
Ground-to-Aerial Person Search: Benchmark Dataset and Approach
Shizhou Zhang, Qingchun Yang, De Cheng +4
In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31,770 images of 260,559 annotated bounding boxes for 2,644 identit…
Prototypical Cross-domain Knowledge Transfer for Cervical Dysplasia Visual Inspection
Yichen Zhang, Yifang Yin, Ying Zhang +3
Early detection of dysplasia of the cervix is critical for cervical cancer treatment. However, automatic cervical dysplasia diagnosis via visual inspection, which is more appropria…
Induction Network: Audio-Visual Modality Gap-Bridging for Self-Supervised Sound Source Localization
Tianyu Liu, Peng Zhang, Wei Huang +3
Self-supervised sound source localization is usually challenged by the modality inconsistency. In recent studies, contrastive learning based strategies have shown promising to esta…
An End-to-End Framework For Universal Lesion Detection With Missing Annotations
Xiaoyu Bai, Yong Xia
Fully annotated large-scale medical image datasets are highly valuable. However, because labeling medical images is tedious and requires specialized knowledge, the large-scale data…
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World
Jiawei Lian, Xiaofei Wang, Yuru Su +2
Patch-based physical attacks have increasingly aroused concerns. However, most existing methods focus on obscuring targets captured on the ground, and some of these methods are sim…