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20162023
most citedProgressive Graph Learning for Open-Set Domain Adaptation

39 citations · 122 across the 12 of their papers we have counts for

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13 papers · 1 filter

cs.CV20234 cited

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…

cs.CV2023

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…

cs.CV20222 cited

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…

cs.CV2021

Mitigating Generation Shifts for Generalized Zero-Shot Learning

Zhi Chen, Yadan Luo, Sen Wang +3

Generalized Zero-Shot Learning (GZSL) is the task of leveraging semantic information (e.g., attributes) to recognize the seen and unseen samples, where unseen classes are not obser…

cs.CV2021

Enhanced Modality Transition for Image Captioning

Ziwei Wang, Yadan Luo, Zi Huang

Image captioning model is a cross-modality knowledge discovery task, which targets at automatically describing an image with an informative and coherent sentence. To generate the c…

cs.CV202038 cited

Adversarial Bipartite Graph Learning for Video Domain Adaptation

Yadan Luo, Zi Huang, Zijian Wang +2

Domain adaptation techniques, which focus on adapting models between distributionally different domains, are rarely explored in the video recognition area due to the significant sp…