The GAN That Warped: Semantic Attribute Editing With Unpaired Data
Garoe Dorta, Sara Vicente, Neill D. F. Campbell, Ivor J. A. Simpson
摘要
Input image (previously unseen) (b) User requested edit: "beak larger than head" (c) User requested edit: "beak smaller than head" Figure 1 : Semantic image editing at high resolution (2480×1850). The user requests a change in a semantic attribute and the input image (a) is automatically transformed by our method into, e.g., an image with "beak larger than head" (b) or "beak smaller than head" (c). The content of the original input, including fine details, is preserved. Our focus is on face editing, as previous work, yet the method is general enough to be applied to other datasets. Please see the supplemental material for videos of these and other edits. (Zoom in for details) 1
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- HoloGAN: Unsupervised Learning of 3D Representations From Natural ImagesThu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt 等ICCV 2019 · 被引用 98 次
- TryOnGAN: body-aware try-on via layered interpolationKathleen M. Lewis, Srivatsan Varadharajan, Ira Kemelmacher-ShlizermanSIGGRAPH 2021 · 被引用 86 次
- Brain-Supervised Image EditingKeith M. Davis, Carlos de la Torre-Ortiz, Tuukka RuotsaloCVPR 2022 · 被引用 17 次
- Not Just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask PredictionDaejin Kim, Mohammad Azam Khan, Jaegul ChooCVPR 2021
- L2M-GAN: Learning To Manipulate Latent Space Semantics for Facial Attribute EditingGuoxing Yang, Nanyi Fei, Mingyu Ding, Guangzhen Liu 等CVPR 2021
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