37 citations · 68 across the 11 of their papers we have counts for
10 papers · 1 filter
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling
Zhuoxiao Chen, Yadan Luo, Zheng Wang +2
Unsupervised domain adaptation (DA) with the aid of pseudo labeling techniques has emerged as a crucial approach for domain-adaptive 3D object detection. While effective, existing…
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error
Zixin Wang, Yadan Luo, Zhi Chen +2
The prevalence of domain adaptive semantic segmentation has prompted concerns regarding source domain data leakage, where private information from the source domain could inadverte…
Zero-Shot Learning by Harnessing Adversarial Samples
Zhi Chen, Pengfei Zhang, Jingjing Li +2
Zero-Shot Learning (ZSL) aims to recognize unseen classes by generalizing the knowledge, i.e., visual and semantic relationships, obtained from seen classes, where image augmentati…
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
Yadan Luo, Zhuoxiao Chen, Zhen Fang +3
Achieving a reliable LiDAR-based object detector in autonomous driving is paramount, but its success hinges on obtaining large amounts of precise 3D annotations. Active learning (A…
Federated Zero-Shot Learning for Visual Recognition
Zhi Chen, Yadan Luo, Sen Wang +2
Zero-shot learning is a learning regime that recognizes unseen classes by generalizing the visual-semantic relationship learned from the seen classes. To obtain an effective ZSL mo…
Deepfake Network Architecture Attribution
Tianyun Yang, Ziyao Huang, Juan Cao +2
With the rapid progress of generation technology, it has become necessary to attribute the origin of fake images. Existing works on fake image attribution perform multi-class class…