解脱
发表于 2025-3-28 15:08:01
http://reply.papertrans.cn/24/2342/234200/234200_41.png
Oafishness
发表于 2025-3-28 18:57:36
http://reply.papertrans.cn/24/2342/234200/234200_42.png
贸易
发表于 2025-3-29 00:53:25
CRAFT: Complementary Recommendation by Adversarial Feature Transformcomplementary recommendation. Our model learns a non-linear transformation between the two manifolds of source and target item categories (e.g., tops and bottoms in outfits). Given a large dataset of images containing instances of co-occurring items, we train a generative transformer network directl
microscopic
发表于 2025-3-29 06:13:41
Full-Body High-Resolution Anime Generation with Progressive Structure-Conditional Generative Adversacharacter images based on structural information. Recent progress in generative adversarial networks with progressive training has made it possible to generate high-resolution images. However, existing approaches have limitations in achieving both high image quality and structural consistency at the
阐释
发表于 2025-3-29 10:04:35
Convolutional Photomosaic Generation via Multi-scale Perceptual Lossesof the mosaic collectively resemble a perceptually plausible image. In this paper, we consider the challenge of automatically generating a photomosaic from an input image. Although computer-generated photomosaicking has existed for quite some time, none have considered simultaneously exploiting colo
渗入
发表于 2025-3-29 14:54:26
http://reply.papertrans.cn/24/2342/234200/234200_46.png
鸵鸟
发表于 2025-3-29 16:52:24
http://reply.papertrans.cn/24/2342/234200/234200_47.png
敌手
发表于 2025-3-29 23:13:52
http://reply.papertrans.cn/24/2342/234200/234200_48.png
寡头政治
发表于 2025-3-30 02:30:12
http://reply.papertrans.cn/24/2342/234200/234200_49.png
忘川河
发表于 2025-3-30 06:08:56
Joint Future Semantic and Instance Segmentation Predictionntly introduced towards better machine intelligence. However, predicting directly in the image color space seems an overly complex task, and predicting higher level representations using semantic or instance segmentation approaches were shown to be more accurate. In this work, we introduce a novel p