Aggregated Contextual Transformations for High-Resolution Image Inpainting

Image inpainting that completes large free-form missing regions in images is a promising yet challenging task. State-of-the-art approaches have achieved significant progress by taking advantage of generative adversarial networks (GAN). However, these approaches can suffer from generating distorted s...

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Veröffentlicht in:	IEEE transactions on visualization and computer graphics Jg. 29; H. 7; S. 3266 - 3280
Hauptverfasser:	Zeng, Yanhong, Fu, Jianlong, Chao, Hongyang, Guo, Baining
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Cognition Context Convolution Discriminators Filling Free form Generative adversarial networks generative adversarial networks (GAN) Generators High resolution Image enhancement image inpainting Image resolution Image synthesis object removal Reasoning State-of-the-art reviews Synthesis Task analysis Texture Training
ISSN:	1077-2626, 1941-0506, 1941-0506
Online-Zugang:	Volltext
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