Eeg332 发表于 2025-3-23 10:01:38
http://reply.papertrans.cn/47/4640/463981/463981_11.png祖先 发表于 2025-3-23 15:10:39
http://reply.papertrans.cn/47/4640/463981/463981_12.pnganarchist 发表于 2025-3-23 21:57:49
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http://reply.papertrans.cn/47/4640/463981/463981_14.pngAccede 发表于 2025-3-24 05:37:11
Sammy Shinaences unseen during training. We propose a pose augmentation method to minimize the training-test gap, a unified paired and unpaired learning strategy to improve the robustness to detection errors, and two-stage network architecture to achieve superior texture quality. To further boost research on t肉体 发表于 2025-3-24 08:17:47
Sammy Shinaat the beginning of their career. We evaluate three methods suited for generating unsupervised style embeddings of images and correlate them with the remaining data. We find no connections between visual style on the one hand and social proximity, gender, and nationality on the other.FOLD 发表于 2025-3-24 12:06:35
http://reply.papertrans.cn/47/4640/463981/463981_17.pngLipoprotein(A) 发表于 2025-3-24 16:13:25
http://reply.papertrans.cn/47/4640/463981/463981_18.pngglans-penis 发表于 2025-3-24 22:02:44
http://reply.papertrans.cn/47/4640/463981/463981_19.png大雨 发表于 2025-3-25 02:00:12
Sammy Shinaetwork on the Dresden database and achieve an overall accuracy of 98.15%, where all the test images are from devices and scenes not used during training to replicate practical applications. The network also outperforms other state-of-the-art CNNs even when the images are manipulated. Furthermore, we