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GANã«é–¢ã™ã‚‹Nyohoã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (34)

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Liquid Warping GAN with Attention ã§ã€å‹•ç”»ã®äººã«åˆã‚ã›ã¦ã€é™æ¢ç”»ã®äººã‚’å‹•ã‹ã™ | cedro-blog
HOMEAIï¼ˆäººå·¥çŸ¥èƒ½ï¼‰Liquid Warping GAN with Attention ã§ã€å‹•ç”»ã®äººã«åˆã‚ã›ã¦ã€é™æ¢ç”»ã®äººã‚’å‹•ã‹ã™ 1.ã¯ã˜ã‚ã« 2018å¹´ã«ã€Everybody Dance Now ã¨ã„ã†ã€ãƒ€ãƒ³ã‚¹ã®é”äººã®å‹•ç”»ãŒã‚ã‚Œã°ã€æ™®é€šã®äººãŒé”äººã¨åŒã˜æ§˜ã«è¸Šã‚‹å‹•ç”»ã‚’ç”Ÿæˆã§ãã‚‹ãƒ‡ã‚£ãƒ¼ãƒ—ãƒ©ãƒ¼ãƒ‹ãƒ³ã‚° ã®æŠ€è¡“ãŒææ¡ˆã•ã‚Œã€ãƒ“ãƒƒã‚¯ãƒªã—ãŸã“ã¨ã‚’è¦šãˆã¦ã„ã¾ã™ã€‚ ãã‚Œã‹ã‚‰2å¹´ãŒçµŒã¡ã€æŠ€è¡“ã¯ã‚‚ã†ä¸€æ®µãƒ¬ãƒ™ãƒ«ã‚¢ãƒƒãƒ—ã—ã¾ã—ãŸã€‚å½“æ™‚ã®å‡ºåŠ›ç”»åƒã¯ãƒœã‚±ãƒœã‚±ã§ã—ãŸãŒã€ã‹ãªã‚Šã‚·ãƒ£ãƒ¼ãƒ—ãªã‚‚ã®ã«æ”¹å–„ã•ã‚Œã¦æ¥ã¾ã—ãŸã€‚ä»Šå›žã¯ã€ãã®æŠ€è¡“ Liquid Warping GAN with Attention ã‚’ã”ç´¹ä»‹ã—ã¾ã™ã€‚ ï¼Šã“ã®è«–æ–‡ã¯ã€2020.11ã«æå‡ºã•ã‚Œã¾ã—ãŸã€‚ 2.Liquid Warping GAN with Attention ã¨ã¯ï¼Ÿ Liquid Warping GAN with Attention ã¨ã¯ã€ãƒªãƒ•ã‚¡
Nyoho 2022/07/07
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GAN
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ãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³å¤‰æ›å™¨ã‚’ä½œã£ãŸè©± - Qiita
ã¯ã˜ã‚ã« ã€Œãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³ã€ã¨å‘¼ã°ã‚Œã‚‹ã€Melvilleã•ã‚“ã®æãã‚¢ã‚¤ã‚³ãƒ³ã¯ãã®ç‹¬ç‰¹ãªä½œé¢¨ã‹ã‚‰å¤§å‹¢ã‹ã‚‰äººæ°—ã‚’é›†ã‚ã¦ã„ã¾ã™ã€‚ ä¸Šã¯Melvilleã•ã‚“ã®ã‚¢ã‚¤ã‚³ãƒ³ã§ã™ã€‚ ã“ã®æ–¹ã¸ã‚¢ã‚¤ã‚³ãƒ³ã®ä½œæˆã‚’ä¾é ¼ã—ã€ãã‚Œã‚’twitterã‚¢ã‚¤ã‚³ãƒ³ã¨ã—ã¦ã„ã‚‹äººãŒã¨ã¦ã‚‚å¤šã„ã“ã¨ã§çŸ¥ã‚‰ã‚Œã¦ã„ã¾ã™ã€‚ ä»£è¡¨çš„ãªãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³ã®ä¾‹ ï¼ˆå·¦ã‹ã‚‰é †ã«ã‚†ã‹ãŸã‚†ã•ã‚“ã€ã¿ãªãŽã•ã‚“ã€ã—ã‚…ã‚“ã—ã‚…ã‚“ã•ã‚“ã®ã‚‚ã®ã§ã™ (2020/12/1ç¾åœ¨)ï¼‰ è‡ªåˆ†ã‚‚ã“ã‚“ãªæ„Ÿã˜ã®ãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³ãŒæ¬²ã—ã„ï¼ï¼ã¨ã„ã†ã“ã¨ã§æ©Ÿæ¢°å¦ç¿’ã§ãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³ç”Ÿæˆå™¨ã‚’å®Ÿè£…ã—ã¾ã—ãŸï¼ï¼.......ã¨ã„ã†ã®ãŒå‰å›žã®å¤§ã¾ã‹ãªã‚ã‚‰ã™ã˜ã§ã™ã€‚ ä»Šå›žã¯åˆ¥ã®æ‰‹æ³•ã‚’ä½¿ã£ã¦ã€ã‚ãƒ£ãƒ©ã®ç”»åƒã‚’ãƒ¡ãƒ«ã‚¢ã‚¤ã‚³ãƒ³ã«å¤‰æ›ã™ã‚‹ãƒ¢ãƒ‡ãƒ«ã‚’å®Ÿè£…ã—ã¾ã—ãŸã€‚ä¾‹ãˆã°ã“ã‚“ãªæ„Ÿã˜ã§å¤‰æ›ã§ãã¾ã™ã€‚ å®Ÿè£…ã—ãŸã‚³ãƒ¼ãƒ‰ã¯ã“ã¡ã‚‰ æœ¬è¨˜äº‹ã§ã¯ã“ã‚Œã«ç”¨ã„ãŸæ‰‹æ³•ã‚’ç´¹ä»‹ã—ã¦ã„ãã¾ã™ã€‚ GANã¨ã¯ ç”»åƒã®å¤‰æ›ã«ã‚ãŸã£ã¦ã¯UGATITã¨ã„ã†æ‰‹æ³•ã‚’ä½¿ã£ã¦
Nyoho 2022/01/03
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GAN
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Taming Transformers for High-Resolution Image Synthesis
Taming Transf ormers for High-Resolution Image Synthesis (a.k.a #VQGAN) Patrick Esser*, Robin Rombach*, BjÃ¶rn Ommer IWR, Heidelberg University CVPR 2021 (ORAL) TL;DR: We introduce the convolutional VQGAN to combine both the efficiency of convolutional approaches with the expressive power of transf ormers, and to combine adversarial with likelihood training in a perceptually meaningful way. The VQGAN
Nyoho 2021/11/30
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GAN
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StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
Nyoho 2021/11/27
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GAN
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GitHub - mchong6/GANsNRoses: Official PyTorch repo for GAN's N' Roses. Diverse im2im and vid2vid selfie to anime translation.
This is the PyTorch implementation of GANs Nâ€™ Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!). Abstract: We show how to learn a map that takes a content code, derived from a face image, and a randomly chosen style code to an anime image. We derive an adversarial loss from our simple and effective definitions of style and content. This adversarial loss guaran
Nyoho 2021/06/20
Guns N' Roses (ã‚¬ãƒ³ã‚ºãƒ»ã‚¢ãƒ³ãƒ‰ãƒ»ãƒãƒ¼ã‚¼ã‚º) ã‹ã‚‰åã¥ã‘ãŸGAN

GAN

PyTorch

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GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds
We present GANcraft, an unsupervised neural rendering framework for generating photorealistic images of large 3D block worlds such as those created in Minecraft. Our method takes a semantic block world as input, where each block is assigned a label such as dirt, grass, tree, sand, or water. We represent the world as a continuous volumetric function and train our model to render view-consistent pho
Nyoho 2021/05/13
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GAN
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Aydao.AI | Art + Machine Learning
Try out the interactive version: This Anime Does Not Exist (link). A custom variant StyleGAN2 model (512px resolution) trained on Danbooru2019. Notable changes include disabling stylemixing during training, forgoing path length regularization, using 2x feature maps, noconst (from the start), top-k (at convergence), and data augmentation using PALM (hands and figures augmentations), among other twe
Nyoho 2021/01/23
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GAN

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GitHub - lucidrains/lightweight-gan: Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
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Nyoho 2020/12/09
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PyTorch

GAN
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æ•°å¤šã®ç”»åƒå¤‰æ›ãŒå¯èƒ½ï¼StyleGANã®æ–°ãŸãªEncoderï¼pixel2Style2pixel
3ã¤ã®è¦ç‚¹ âœ”ï¸ ç¾å®Ÿç”»åƒã‚’StyleGANã®æ½œåœ¨ç©ºé–“ã«åŸ‹ã‚è¾¼ã‚€Encoderã€ŒpSpã€ã®ææ¡ˆ âœ”ï¸ æ§˜ã€…ãªç”»åƒå¤‰æ›ã‚¿ã‚¹ã‚¯ã«å¿œç”¨å¯èƒ½ âœ”ï¸ StyleGANã®å¤šæ§˜æ€§ã‚’åˆ©ç”¨ Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation written byÂ Elad Richardson,Â Yuval Alaluf,Â Or Patashnik,Â Yotam Nitzan,Â Yaniv Azar,Â Stav Shapiro,Â Daniel Cohen-Or (Submitted on 3 Aug 2020) Comments: Published by arXiv Subjects:Â Â Computer Vision and Pattern Recognition (cs.CV) Code ã¯ã˜ã‚ã« é«˜å“è³ªãªç”»åƒã‚’ç”Ÿæˆ
Nyoho 2020/09/16
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GAN
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Innovative Techï¼š ã“ã®ã‚³ãƒ¼ãƒŠãƒ¼ã§ã¯ã€ãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼ã®æœ€æ–°ç ”ç©¶ã‚’ç´¹ä»‹ã™ã‚‹Webãƒ¡ãƒ‡ã‚£ã‚¢ã€ŒSeamlessã€ã‚’ä¸»å®°ã™ã‚‹å±±ä¸‹è£•æ¯…æ°ãŒåŸ·ç†ã€‚æ–°è¦æ€§ã®é«˜ã„ç§‘å¦è«–æ–‡ã‚’å±±ä¸‹æ°ãŒãƒ”ãƒƒã‚¯ã‚¢ãƒƒãƒ—ã—ã€è§£èª¬ã™ã‚‹ã€‚ åŒ—äº¬èˆªç©ºèˆªå¤©å¤§å¦ã€ä¸å›½ç§‘å¦é™¢ã€ã‚·ãƒ³ã‚¬ãƒãƒ¼ãƒ«å›½ç«‹å¤§å¦ã€ã‚·ãƒ³ã‚¬ãƒãƒ¼ãƒ«YITU Techno logyã«ã‚ˆã‚‹ç ”ç©¶ãƒãƒ¼ãƒ ãŒé–‹ç™ºã—ãŸ ã€ŒPSGANã€ã¯ã€ç”»åƒã«å†™ã‚‹äººã®é¡”ã®åŒ–ç²§ã‚’åˆ¥ã®ç”»åƒå†…ã®é¡”ã¸è»¢å†™ã™ã‚‹ã€æ·±å±¤å¦ç¿’ã‚’ç”¨ã„ãŸæ‰‹æ³•ã ã€‚è¡¨æƒ…ã‚„ãƒãƒ¼ã‚ºãŒãã‚Œãžã‚Œé•ã£ã¦ã‚‚åŒ–ç²§ã ã‘ã‚’è»¢å†™ã§ãã‚‹ã€‚ ã“ã‚Œã¾ã§ã‚‚ãƒ¡ã‚¤ã‚¯ã‚¢ãƒƒãƒ—ã‚’ç•°ãªã‚‹ç”»åƒã§è»¢å†™ã™ã‚‹ç ”ç©¶ã¯è¡Œã‚ã‚Œã¦ãŠã‚Šæˆæžœã‚‚å‡ºã¦ã„ãŸãŒã€ãƒãƒ¼ã‚ºã‚„è¡¨æƒ…ã®é•ã„ãŒå¤§ãã„ç”»åƒé–“ã§ã¯ä¾ç„¶ã¨ã—ã¦å›°é›£ã§ã€é¡”ã®å‘ããŒå¸¸ã«å¤‰åŒ–ã™ã‚‹å‹•ç”»ã¸ã®è»¢ç§»ã¯ã•ã‚‰ã«é›£ã—ã‹ã£ãŸã€‚ã•ã‚‰ã«åŒ–ç²§ã®æ¿ƒæ·¡ã‚’åˆ¶å¾¡ã§ãã‚‹ã‚ˆã†ãªã‚«ã‚¹ã‚¿ãƒžã‚¤ã‚ºã¯ã§ããšã€è»¢ç§»ã™ã‚‹éƒ¨åˆ†ã¯æŒ‡å®šã§ããªã„ãªã©ã€å¿œç”¨ç¯„å›²ã¯é™ã‚‰ã‚Œã¦ã„ãŸã€‚ ã“ã‚Œã‚‰ã®å•é¡Œã‚’è§£æ±ºã™ã‚‹ãŸã‚
Nyoho 2020/07/10
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GitHub - adjidieng/PresGANs: Prescribed Generative Adversarial Networks
Nyoho 2020/07/01
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PyTorch

GAN
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GitHub - t-ae/vgan-s4tf
Nyoho 2020/03/11
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Swift

GAN
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FGO StyleGAN: This Heroic Spirit Doesnâ€™t Exist
When I first saw Nvidiaâ€™s StyleGANâ€™s results I felt like it looked like a bunch of black magic. I am not as experienced in the area of GANs as other parts of deep learning, this lack of experience and the thought that I really lacked the GPU firepower to train up my own StyleGAN stopped me from jumping in sooner. For scale, on the StyleGAN github Nvidia lists the GPU specifications, basically sayi
Nyoho 2019/12/28
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GAN
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GitHub - NVlabs/stylegan2: StyleGAN2 - Official TensorFlow Implementation
Analyzing and Improving the Image Quality of StyleGAN Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila Paper: http://arxiv.org/abs/1912.04958 Video: https://youtu.be/c-NJtV9Jvp0 Abstract: The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its charact
Nyoho 2019/12/13
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GAN
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GANã®æ¦‚è¦ã¨DCGANã®ã‚¢ãƒ¼ã‚ãƒ†ã‚¯ãƒãƒ£ï¼ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ
74. . Deep Learningâ€•Python , 2016 ! PyTorch , 2019 Goodfellow, Ian, et al. Generative adversarial nets., Advances in neural information processing systems. 2014 Radford, Alec, Luke Metz, Soumith Chintala. Unsupervised representation learning with deep convolutional generative adversarial networks.,Â arXiv preprint, arXiv:1511.06434. 2015 Thank you! 75. Thank you! CS231n Winter 2016: Lecture 13: Seg
Nyoho 2019/10/30
GAN

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TensorFlow2.0 + ç„¡æ–™ã®Colab TPUã§DCGANã‚’å®Ÿè£…ã—ãŸ - Qiita
TensorFlow2.0ã¨Google Colaboratoryã®ç„¡æ–™TPUã‚’ä½¿ã£ã¦ã€DCGANã‚’å®Ÿè£…ã—ã¾ã—ãŸã€‚ è¨“ç·´çµŒéŽã®æ§˜å pic.twitter.com/2qXowYMk6t â€” ã—ã“ã‚ã‚“@ã€Žãƒ¢ã‚¶ã‚¤ã‚¯é™¤åŽ»æœ¬ã€å¥½è©•é€šè²©ä¸ (@koshian2) October 21, 2019 ä½•ã‚’ã‚„ã£ãŸã‹ Google Colabã®TPUï¼‹TF2.0ã§CelebAï¼ˆç´„20ä¸‡æžšï¼‰ã‚’DCGANã§ç”Ÿæˆ TF1.Xç³»ã®TPUã§ã¯ã€åŒæ™‚ã«å®Ÿè¡Œå¯èƒ½ãªã‚°ãƒ©ãƒ•ã¯1å€‹ã®åˆ¶ç´„ãŒã‚ã£ãŸãŸã‚ã€GANã®è¨“ç·´ãŒå®¹æ˜“ã§ã¯ãªã‹ã£ãŸï¼ˆã“ã¡ã‚‰ã®è¨˜äº‹ã«ã‚ã‚‹é€šã‚Šã€ä¸å¯èƒ½ã§ã‚ã£ãŸã‚ã‘ã§ã¯ãªã„ã€‚ã—ã‹ã—ã€ä½Žãƒ¬ãƒ™ãƒ«APIãŒå¿…é ˆã§æ±ºã—ã¦å®¹æ˜“ã§ã¯ãªã‹ã£ãŸï¼‰ã€‚TF2.Xç³»ã®TPUã§ã¯ã€ã‚‚ã£ã¨å®¹æ˜“ã«GANã‚’å®Ÿè£…ã§ããŸã€‚ DCGANã®è«–æ–‡é€šã‚Šã®ãƒ¢ãƒ‡ãƒ«ï¼ˆãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ãƒ¼æ•°ï¼šG=12.7M, D=11.0Mï¼‰ã§ã€‚64x64ã®ç”»åƒ20ä¸‡æžšã‚’ã€1ã‚¨ãƒãƒƒã‚¯ã‚’40ç§’ç¨‹
Nyoho 2019/10/24
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GAN
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Generated Photos | Unique, worry-free model photos
Generate unique, expressive AI-generated faces in real time
Nyoho 2019/10/19
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GAN
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ä¸–ç•Œåˆï¼GANã®ãƒ¢ãƒ‡ãƒ«ã‚’è‡ªå‹•ã§ç”Ÿæˆã™ã‚‹AutoGAN | AI-SCHOLAR
3ã¤ã®è¦ç‚¹ GANã®ãƒ¢ãƒ‡ãƒ«ã‚’è‡ªå‹•ç”Ÿæˆã™ã‚‹ä¸–ç•Œã§åˆã‚ã¦ã®æ‰‹æ³• å¾“æ¥ã®GANã®æ‰‹æ³•ã‚ˆã‚Šã‚‚é«˜ç²¾åº¦ãªç”»åƒã®ç”ŸæˆãŒå¯èƒ½ Multi-Level Architecture Searchã‚„ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã®ãƒªã‚»ãƒƒãƒˆã‚’è¡Œã†ã“ã¨ã§é«˜é€Ÿãªå¦ç¿’ãŒå¯èƒ½ ã¿ãªã•ã‚“ã¯Neural Architecture Search (NAS) ã¨ã„ã†æ‰‹æ³•ã‚’ã”å˜çŸ¥ã§ã—ã‚‡ã†ã‹ï¼Ÿ æ™®é€šã®Deep Learningã§ã¯ã€ãƒ¢ãƒ‡ãƒ«ã®æ§‹é€ ã¯äººé–“ãŒæŒ‡å®šã—ã€ãƒ¢ãƒ‡ãƒ«ã®ãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã®ã¿ã‚’æœ€é©åŒ–ã—ã¾ã™ãŒã€NASã§ã¯ãƒ¢ãƒ‡ãƒ«æ§‹é€ ã‚‚å«ã‚ã¦æœ€é©åŒ–ã‚’è¡Œã„ã¾ã™ã€‚ãã®ãŸã‚ã‚ˆã‚Šé«˜ç²¾åº¦ãªãƒ¢ãƒ‡ãƒ«ã‚’ç”Ÿæˆã™ã‚‹ã“ã¨ãŒå¯èƒ½ã§ã™ãŒã€å¦ç¿’æ™‚é–“ãŒå¤§ãããªã£ã¦ã—ã¾ã†æ¬ ç‚¹ã‚‚ã‚ã‚Šã¾ã™ã€‚ ã¤ã„1,2å¹´ã»ã©å‰ã¾ã§ã¯ã€NASã¯ä½•åå°ã‚‚GPUã‚’ä½¿ã£ã¦ä½•é€±é–“ã‚‚ã‹ã‘ã¦è¡Œãªã£ã¦ã„ã¾ã—ãŸãŒã€æœ€è¿‘ã§ã¯GPU1å°ã§4æ™‚é–“ã§å¦ç¿’ã§ãã‚‹NASã‚‚ç™»å ´ã™ã‚‹ãªã©ã€æ³¨ç›®ã‚’é›†ã‚ã¦ã„ã¾ã™ã€‚ ä»Šå›žç´¹ä»‹ã™ã‚‹AutoGANã¯ã€ã“ã®NASã®æ‰‹
Nyoho 2019/09/13
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GAN
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Generative Dog Images
Nyoho 2019/08/17
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GAN
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i96_1e-4_6e_4_bs32_195
Explore and run machine learning code with Kaggle Notebooks | Using data from Generative Dog Images
Nyoho 2019/08/16
GAN
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