total number : 3 Towards Robust Face Recognition with Comprehensive Search 论文/Paper: http://arxiv.org/pdf/2208.13600 代码/Code: None CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions 论文/Paper: http://arxiv.org/pdf/2208.13528 代码/Code: None Towards Rea...
代码/Code: https://github.com/lxtGH/Video-K-Net GAN - 2 篇 Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data 标题:自然图像中的共性救援GANS:预先利用通用和无自由的合成数据 论文/Paper: http://arxiv.org/pdf/2204.04950 ...
这篇论文入选了今年10月在威尼斯举办的国际计算机视觉大会ICCV 2017，要进行口头报告，相应的源代码在GitHub上已经收获了402个星，月初还登顶了GitHub热门项目Python排行榜。现实，梦境 康奈尔大学计算机系副教授Noah Snavely深受打动，他说，创建逼真的人工场景非常困难，即便是当今最好的方法也无法做到，而陈奇峰的系统生成...
说到GAN第一篇要看的paper当然是Ian Goodfellow大牛的Generative Adversarial Networks(arxiv:https://arxiv.org/abs/1406.2661),这篇paper算是这个领域的开山之作。 GAN的基本原理其实非常简单,这里以生成图片为例进行说明。假设我们有两个网络,G(Generator)和D(Discriminator)。正如它的名字所暗示的那样,它们的功能...
Code：https://github.com/eriklindernoren/Keras-GAN/blob/master/pix2pix/pix2pix.pyPaper:Image-to-Image Translation with Conditional Adversarial NetworksPhillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efroshttps://arxiv.org/abs/1611.07004Pix2Pix目前有开源的Torch、PyTorch、TensorFlow、Chainer...
GAN implementation hacksSalimans paper & ChintalaWorld researchlinkpaper DCGAN : Unsupervised Representation Learning with Deep Convolutional Generative Adversarial NetworksRadford & et al.ICLR 2016linkpaper64x64 human ProGAN:Progressive Growing of GANs for Improved Quality, Stability, and VariationTero Karra...
按照ICMIR 2019 Tutorial- Generating Music with GANs—An Overview and Case Studies中梳理的结构进行整理 I. 符号化的音乐生成 [ICML 2016] C-RNN-GAN: Continuous recurrent neural networks with adversarial training (paper)(code) key:连续的音乐表示;RNN结构的GAN模型 [ISMIR 2017] MidiNet: A convolutional...
代码/Code: https://github.com/lxtGH/Video-K-Net GAN - 2 篇 Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data 标题:自然图像中的共性救援GANS:预先利用通用和无自由的合成数据 论文/Paper: http://arxiv.org/pdf/2204.04950 ...
Cannot find the paper you are looking for? You can Submit a new open access paper. Contact us on: hello@paperswithcode.com . Papers With Code is a free resource with all data licensed under CC-BY-SA. Terms Data policy Cookies policy from ...
†: numbers from the original paper, as training diverged with the BigGAN opensourced code. Parse references Res. ↓FID ↑IS BigGAN* Brock et al. 64 12.3 ± 0.0 27.0 ± 0.2 BigGAN* Brock et al. + DA (d) 64 10.2 ± 0.1 30.1 ± 0.1 IC-GAN 64 8.5 ± 0.0 39.7 ± 0.2 IC-...