GRIG:Data-efficient generative residual image inpaintingOA
GRIG:Data-efficient generative residual image inpainting
Wanglong Lu;Xianta Jiang;Xiaogang Jin;Yong-Liang Yang;Minglun Gong;Kaijie Shi;Tao Wang;Hanli Zhao
Key Laboratory of Intelligent Informatics of Safety & Emergency of Zhejiang Province,Wenzhou University,Wenzhou 325035,China||Department of Computer Science,Memorial University of Newfoundland,St.John's,NL A1B 3X5,CanadaDepartment of Computer Science,Memorial University of Newfoundland,St.John's,NL A1B 3X5,CanadaState Key Laboratory of CAD&CG,Zhejiang University,Hangzhou 310058,ChinaDepartment of Computer Science,University of Bath,Bath BA2 7AY,UKSchool of Computer Science University of Guelph Guelph,ON N1G 2W1,CanadaKey Laboratory of Intelligent Informatics of Safety & Emergency of Zhejiang Province,Wenzhou University,Wenzhou 325035,China||Department of Computer Science,Memorial University of Newfoundland,St.John's,NL A1B 3X5,CanadaDepartment of Computer Science and Technology,Nanjing University,Nanjing,ChinaKey Laboratory of Intelligent Informatics of Safety & Emergency of Zhejiang Province,Wenzhou University,Wenzhou 325035,China
image inpaintingiterative reasoningresidual learninggenerative adversarial networks
image inpaintingiterative reasoningresidual learninggenerative adversarial networks
《计算可视媒体（英文）》 2025 (6)
1329-1361,33
This work was supported by the Zhejiang Provincial Natural Science Foundation of China(Grant No.LZ21F020001)and the Basic Scientific Research Program of Wenzhou(Grant No.S20220018).
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