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Acknowledgements
This work was supported by the Fundamental Research Funds for the Central Universities 07063233084, the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 62206134), and the Tianjin Key Laboratory of Visual Computing and Intelligent Perception (VCIP). Computation is supported by the Supercomputing Center of Nankai University (NKSC).
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Yuxuan Li is a research assistant at Nankai University, China. He graduated from University College London (UCL) with a first-class degree in computer science. He was champion of the Second Jittor Artificial Intelligence Challenge and was awarded 2nd place in Facebook Hack-a-Project and the Greater Bay Area International Algorithm Competition in 2022. His research interests include computer vision, image generation, and remote sensing object detection.
Lingfeng Yang received his B.S. degree from Nanjing University of Science and Technology, China, in 2020. He is currently a Ph.D. student at the Department of Computer Science and Engineering, Nanjing University of Science and Technology. His research interests include object detection, defect detection, and fine-grained visual categorization.
Xiang Li is an associate professor at the College of Computer Science, Nankai University. He obtained his Ph.D. degree from Nanjing University of Science and Technology, China, in 2020. His research interests include CNN/Transformer backbone, object detection, knowledge distillation, and self-supervised learning. He has published 20+ papers in top journals and conferences, such as T-PAMI, CVPR, and NeurIPS.
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Li, Y., Yang, L. & Li, X. APF-GAN: Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network. Comp. Visual Media 10, 187–192 (2024). https://doi.org/10.1007/s41095-023-0357-1
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DOI: https://doi.org/10.1007/s41095-023-0357-1