Image Generation Papers

作者: 西方失败9527 | 来源:发表于2017-10-21 12:48 被阅读0次

    Optimizing Neural Networks That Generate Images(2014. PhD thesis)

    paper :http://www.cs.toronto.edu/~tijmen/tijmen_thesis.pdf

    github:https://github.com/mrkulk/Unsupervised-Capsule-Network

    Learning to Generate Chairs, Tables and Cars with Convolutional Networks

    arxiv:http://arxiv.org/abs/1411.5928

    code,demo&data:http://lmb.informatik.uni-freiburg.de/resources/software.php

    raw data(3GB):http://www.di.ens.fr/willow/research/seeing3Dchairs/data/rendered_chairs.tar

    Generative Adversarial Networks Generative Adversarial Nets

    arxiv:http://arxiv.org/abs/1406.2661

    paper:https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf

    github:https://github.com/goodfeli/adversarial

    github:https://github.com/aleju/cat-generator

    DRAW: A Recurrent Neural Network For Image Generation (Google DeepMind)

    arxiv:http://arxiv.org/abs/1502.04623

    github:https://github.com/vivanov879/draw

    github(Theano):https://github.com/jbornschein/draw

    github(Lasagne):https://github.com/skaae/lasagne-draw

    youtube:https://www.youtube.com/watch?v=Zt-7MI9eKEo&hd=1

    video:http://pan.baidu.com/s/1gd3W6Fh

    Understanding and Implementing Deepmind’s DRAW Model

    blog:http://evjang.com/articles/draw

    github:https://github.com/ericjang/draw

    Generative Image Modeling Using Spatial LSTMs

    arxiv:http://arxiv.org/abs/1506.03478

    github:https://github.com/lucastheis/ride/

    Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks(NIPS 2015)

    arxiv:http://arxiv.org/abs/1506.05751

    code:http://soumith.ch/eyescream/

    project page:http://soumith.ch/eyescream/

    homepage:http://www.cs.nyu.edu/~denton/

    Conditional generative adversarial nets for convolutional face generation

    paper:http://www.foldl.me/uploads/2015/conditional-gans-face-generation/paper.pdf

    blog:http://www.foldl.me/2015/conditional-gans-face-generation/

    github:https://github.com/hans/adversarial

    Generating Images from Captions with Attention

    arxiv:http://arxiv.org/abs/1511.02793

    github:https://github.com/emansim/text2image

    demo:http://www.cs.toronto.edu/~emansim/cap2im.html

    Attribute2Image: Conditional Image Generation from Visual Attributes

    arxiv:http://arxiv.org/abs/1512.00570

    Deep Visual Analogy-Making

    paper:https://papers.nips.cc/paper/5845-deep-visual-analogy-making.pdf

    code:http://www-personal.umich.edu/~reedscot/files/nips2015-analogy.tar.gz

    data:http://www-personal.umich.edu/~reedscot/files/nips2015-analogy-data.tar.gz

    slides:http://www-personal.umich.edu/~reedscot/files/nips2015-analogy-slides.pptx

    Autoencoding beyond pixels using a learned similarity metric

    arxiv:http://arxiv.org/abs/1512.09300

    demo:http://algoalgebra.csa.iisc.ernet.in/deepimagine/

    github:https://github.com/andersbll/autoencoding_beyond_pixels

    video:http://video.weibo.com/show?fid=1034:f00b4e5a34e8c1ebe78ccd00da95f9e0

    github:https://github.com/stitchfix/fauxtograph

    Deep Visual Analogy-Making

    paper:https://papers.nips.cc/paper/5845-deep-visual-analogy-making

    github(Tensorflow):https://github.com/carpedm20/visual-analogy-tensorflow

    slides:http://slideplayer.com/slide/9147672/

    mirror:http://pan.baidu.com/s/1pKgrdnt

    PixelRNN

    Pixel Recurrent Neural Networks (Google DeepMind. ICML 2016 best paper)

    arxiv:http://arxiv.org/abs/1601.06759

    github:https://github.com/igul222/pixel_rnn

    notes(by Hugo Larochelle):https://www.evernote.com/shard/s189/sh/fdf61a28-f4b6-491b-bef1-f3e148185b18/aba21367d1b3730d9334ed91d3250848

    video(by Hugo Larochelle):https://www.periscope.tv/hugo_larochelle/1ypKdnMkjBnJW

    Generating images with recurrent adversarial networks

    arxiv:http://arxiv.org/abs/1602.05110

    github:https://github.com/jiwoongim/GRAN

    Generative Adversarial Text to Image Synthesis (ICML 2016)

    arxiv:http://arxiv.org/abs/1605.05396

    project page:https://www.mpi-inf.mpg.de/departments/computer-vision-and-multimodal-computing/research/embeddings-for-image-classification/generative-adversarial-text-to-image-synthesis/

    github:https://github.com/reedscot/icml2016

    code+dataset:http://datasets.d2.mpi-inf.mpg.de/akata/cub_txt.tar.gz

    PixelCNN

    Conditional Image Generation with PixelCNN Decoders (Google DeepMind. PixelCNN 2.0)

    arxiv:http://arxiv.org/abs/1606.05328

    Inverting face embeddings with convolutional neural networks

    arxiv:http://arxiv.org/abs/1606.04189

    github:https://github.com/pavelgonchar/face-transfer-tensorflow

    Deep Generative Model

    Digit Fantasies by a Deep Generative Model

    demo:http://www.dpkingma.com/sgvb_mnist_demo/demo.html

    Conditional generative adversarial nets for convolutional face generation

    paper:http://www.foldl.me/uploads/2015/conditional-gans-face-generation/paper.pdf

    blog:http://www.foldl.me/2015/conditional-gans-face-generation/

    github:https://github.com/hans/adversarial

    Max-margin Deep Generative Models

    arxiv:http://arxiv.org/abs/1504.06787

    github:https://github.com/zhenxuan00/mmdgm

    Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks (NIPS 2015)

    arxiv:http://arxiv.org/abs/1506.05751

    code:http://soumith.ch/eyescream/

    project page:http://soumith.ch/eyescream/

    homepage:http://www.cs.nyu.edu/~denton/

    notes:http://colinraffel.com/wiki/deep_generative_image_models_using_a_laplacian_pyramid_of_adversarial_networks

    Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks(CatGAN)

    arxiv:http://arxiv.org/abs/1511.06390

    Torch convolutional GAN: Generating Faces with Torch

    blog:http://torch.ch/blog/2015/11/13/gan.html

    github:https://github.com/skaae/torch-gan

    DCGAN

    Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (DCGAN)

    arxiv:http://arxiv.org/abs/1511.06434

    github:https://github.com/jazzsaxmafia/dcgan_tensorflow

    github:https://github.com/Newmu/dcgan_code

    github:https://github.com/mattya/chainer-DCGAN

    github:https://github.com/soumith/dcgan.torch

    github:https://github.com/carpedm20/DCGAN-tensorflow

    Discriminative Regularization for Generative Models

    arxiv:http://arxiv.org/abs/1602.03220

    github:https://github.com/vdumoulin/discgen

    Auxiliary Deep Generative Models

    arxiv:http://arxiv.org/abs/1602.05473

    One-Shot Generalization in Deep Generative Models (Google DeepMind. ICML 2016)

    arxiv:http://arxiv.org/abs/1603.05106

    Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet

    project page:http://www.stat.ucla.edu/~jxie/STGConvNet/STGConvNet.html

    paper:http://www.stat.ucla.edu/~jxie/STGConvNet/STGConvNet_file/doc/STGConvNet.pdf

    3D

    Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis (NIPS 2015)

    paper:http://www-personal.umich.edu/~reedscot/nips15_rotator_final.pdf

    Blogs

    Generative Adversarial Autoencoders in Theano

    blog:https://swarbrickjones.wordpress.com/2016/01/24/generative-adversarial-autoencoders-in-theano/

    github:https://github.com/mikesj-public/dcgan-autoencoder

    Torch convolutional GAN: Generating Faces with Torch

    blog:http://torch.ch/blog/2015/11/13/gan.html

    github:https://github.com/skaae/torch-gan

    Generating Large Images from Latent Vectors

    http://blog.otoro.net/2016/04/01/generating-large-images-from-latent-vectors/

    Generative Adversarial Network Demo for Fresh Machine Learning #2

    youtube:https://www.youtube.com/watch?v=deyOX6Mt_As&feature=em-uploademail

    github:https://github.com/llSourcell/Generative-Adversarial-Network-Demo

    demo:http://cs.stanford.edu/people/karpathy/gan/

    Projects

    Generate cat images with neural networks

    github:https://github.com/aleju/cat-generator

    TF-VAE-GAN-DRAW

    intro: A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).

    github:https://github.com/ikostrikov/TensorFlow-VAE-GAN-DRAW

    Generating Large Images from Latent Vectors

    project page:http://blog.otoro.net/2016/04/01/generating-large-images-from-latent-vectors/

    github:https://github.com/hardmaru/cppn-gan-vae-tensorflow

    Generating Large Images from Latent Vectors - Part Two

    project page:http://blog.otoro.net/2016/06/02/generating-large-images-from-latent-vectors-part-two/

    github:https://github.com/hardmaru/resnet-cppn-gan-tensorflow

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