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20182023
most citedLearning Domain Adaptive Object Detection with Probabilistic Teacher

33 citations · 66 across the 18 of their papers we have counts for

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Showing 2022Show all

8 papers · 1 filter

cs.CV2022★ 3 cited

Attention Diversification for Domain Generalization

Rang Meng, Xianfeng Li, Weijie Chen +7

Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…

cs.CV2022

Universal Domain Adaptive Object Detector

Wenxu Shi, Lei Zhang, Weijie Chen +1

Universal domain adaptive object detection (UniDAOD)is more challenging than domain adaptive object detection (DAOD) since the label space of the source domain may not be the same…

cs.CV2022

Slimmable Domain Adaptation

Rang Meng, Weijie Chen, Shicai Yang +7

Vanilla unsupervised domain adaptation methods tend to optimize the model with fixed neural architecture, which is not very practical in real-world scenarios since the target data…

cs.CV2022★ 3 cited

Label Matching Semi-Supervised Object Detection

Binbin Chen, Weijie Chen, Shicai Yang +6

Semi-supervised object detection has made significant progress with the development of mean teacher driven self-training. Despite the promising results, the label mismatch problem…

cs.CV2022★ 33 cited

Learning Domain Adaptive Object Detection with Probabilistic Teacher

Meilin Chen, Weijie Chen, Shicai Yang +8

Self-training for unsupervised domain adaptive object detection is a challenging task, of which the performance depends heavily on the quality of pseudo boxes. Despite the promisin…

cs.CV2022

Transductive CLIP with Class-Conditional Contrastive Learning

Junchu Huang, Weijie Chen, Shicai Yang +3

Inspired by the remarkable zero-shot generalization capacity of vision-language pre-trained model, we seek to leverage the supervision from CLIP model to alleviate the burden of da…

cs.CV2022★ 1 cited

2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach

Yilu Guo, Shicai Yang, Weijie Chen +3

Convolutional neural networks (CNNs) have achieved significant success in image classification by utilizing large-scale datasets. However, it is still of great challenge to learn f…

cs.LG2022★ 5 cited

Dynamic Domain Generalization

Zhishu Sun, Zhifeng Shen, Luojun Lin +4

Domain generalization (DG) is a fundamental yet very challenging research topic in machine learning. The existing arts mainly focus on learning domain-invariant features with limit…