风格和样式在GAN网络中的分离(Style and Content Disentanglement in Generative Adversarial Networks)CVPR 2019,程序员大本营,技术文章内容聚合第一站。
Experiments show that GOYA explicitly learns to represent the two artistic dimensions (content and style) of the original artistic image, paving the way for leveraging generative models in art analysis.doi:10.3390/jimaging10070156Yankun WuYuta NakashimaNoa GarciaJournal of Imaging...
Thanks to the proposed novel disentanglement and data augmentation techniques, HOOD can effectively deal with OOD examples in unknown and open environments, whose effectiveness is empirically validated in three typical OOD applications including OOD detection, open-set semi-supervised learning, and open-...
Inter-Domain Invariant Cross-Domain Object Detection Using Style and Content Disentanglement for In-Vehicle Images The accurate detection of relevant vehicles, pedestrians, and other targets on the road plays a crucial role in ensuring the safety of autonomous driving. ... Z Jiang,Y Zhang,Z Wang...
Paper tables with annotated results for Measuring the Biases and Effectiveness of Content-Style Disentanglement
Experiments show that GOYA explicitly learns to represent the two artistic dimensions (content and style) of the original artistic image, paving the way for leveraging generative models in art analysis.Yankun WuYuta NakashimaNoa Garcia
This is achieved by introducing two novel losses: a fixpoint triplet style loss to learn subtle variations within one style or between different styles and a disentanglement loss to ensure that the stylization is not conditioned on the real input photo. In addition the paper proposes various ...
Fine-Grained Style Modeling, Transfer and Prediction in Text-to-Speech Synthesis via Phone-Level Content-Style Disentanglementdoi:10.21437/INTERSPEECH.2021-1129Daxin TanTan LeeISCAConference of the International Speech Communication Association
Representation Learning for Style and Content Disentanglement with AutoencodersMany approaches have been proposed to disentangle the style and content from image representations. Most existing methods aim to create new images from the combinations of separated style and......
Inter-Domain Invariant Cross-Domain Object Detection Using Style and Content Disentanglement for In-Vehicle Imagesdoi:10.3390/rs16020304CONVOLUTIONAL neural networksTRANSFORMER modelsTRAFFIC safetyDETECTORSThe accurate detection of relevant vehicles, pedestrians, and other targets on the road plays a...