Semantic consistency knowledge transfer for unsupervised cross domain object detection
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Sichuan Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05713-6.pdf
Reference72 articles.
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2. Hu D, Wei Y, Qian R, Lin W, Song R, Wen J-R (2022) Class-aware sounding objects localization via audiovisual correspondence. IEEE Trans Pattern Anal Mach Intell 44(12):9844–9859
3. Xu Y, Zhou C, Yu X, Xiao B, Yang Y (2021) Pyramidal multiple instance detection network with mask guided self-correction for weakly supervised object detection. IEEE Trans Image Process 30:3029–3040
4. Tao R, Li H, Wang T, Wei Y, Ding Y, Jin B, Zhi H, Liu X, Liu A (2022) Exploring endogenous shift for cross-domain detection: a large-scale benchmark and perturbation suppression network. In: 2022 IEEE/CVF conference on computer vision and pattern recognition (CVPR), pp 21157–21167
5. Prabhu V, Khare S, Kartik D, Hoffman J (2021) SENTRY: selective entropy optimization via committee consistency for unsupervised domain adaptation. In: 2021 IEEE/CVF international conference on computer vision (ICCV), pp 8538–8547
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