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A curated list of awesome deep vision web demo
| Date | Stars |
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| 2026-07-24 | 349 |
| 2026-07-25 | 349 |
| 2026-07-28 | 349 |
| 2026-07-30 | 349 |
| 2026-08-06 | 349 |
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# awesome-deep-vision-web-demo A curated list of awesome deep vision web demo ## Contributing Please feel free to pull requests to add papers. ## Vision Demo List ### Hand-written Digit Recognition * https://tensorflow-mnist.herokuapp.com/ * https://erkaman.github.io/regl-cnn/src/demo.html * https://transcranial.github.io/keras-js/#/mnist-cnn ### Image Segmentation * CRF+RNN (ICCV 2015) http://www.robots.ox.ac.uk/~szheng/crfasrnndemo ### Image Classification * VGG-16 https://deeplearning4j.org/demo-classifier-vgg16 * Illustration2vec http://demo.illustration2vec.net/ * Leiden Univ. http://goliath.liacs.nl/ * Clarifai https://www.clarifai.com/demo * Google Colud Vision API http://vision-explorer.reactive.ai/#/?_k=aodf68 * IBMWatson Vision API https://visual-recognition-demo.mybluemix.net/ * Karpathy: MNIST ConvNet http://cs.stanford.edu/people/karpathy/convnetjs/demo/mnist.html * Karpathy: CIFAR10 ConvNet http://cs.stanford.edu/people/karpathy/convnetjs/demo/cifar10.html * keras-js: IMAGENET 50-layer Residual Network https://transcranial.github.io/keras-js/#/resnet50 * keras-js: IMAGENET Inception-v3 https://transcranial.github.io/keras-js/#/inception-v3 * keras-js: IMAGENET SqueezeNet v1.1 https://transcranial.github.io/keras-js/#/squeezenet-v1.1 * Teachable Machine: 3 Classes with online video https://teachablemachine.withgoogle.com/ ### Object Detection * http://silverpond.com.au/object-detector ### Text Detection * Single Shot Text Detector with Regional Attention (ICCV 2017) http://128.227.246.42:5555/ ### Age Estimation * https://how-old.net/ ### AutoEncoder * VAE : MNIST Geneartation http://www.dpkingma.com/sgvb_mnist_demo/demo.html * VAE : keras-js MNIST https://transcranial.github.io/keras-js/#/mnist-vae * VAE : Gray Face Generation http://vdumoulin.github.io/morphing_faces/online_demo.html * Karpathy: Denoising AutoEncoder http://cs.stanford.edu/people/karpathy/convnetjs/demo/autoencoder.html ### GAN * GAN : 1D Gaussian Distribution Fitting http://cs.stanford.edu/people/karpathy/gan/ * DCGAN : Asian Color Face Generation http://carpedm20.github.io/faces/ * DCGAN : Character Generation http://mattya.github.io/chainer-DCGAN/ * ACGAN : keras-js MNIST https://transcranial.github.io/keras-js/#/mnist-acgan * Girls Chacacter Generation : http://make.girls.moe/#/ * GAN-playground : https://reiinakano.github.io/gan-playground/ * GA Lab : https://poloclub.github.io/ganlab/ * Style GAN : https://thispersondoesnotexist.com/ * GauGAN : http://52.12.58.174/ ### Style Transfer * On/Off-line Style Transfer, Deep Dream https://deepdreamgenerator.com/gallery * Offline Style Transfer, http://demos.algorithmia.com/deep-style/ ### Image Translation * pix2pix https://affinelayer.com/pixsrv/index.html * pix2pix (human face) http://fotogenerator.npocloud.nl/ ### Colorization * sketch to color image https://paintschainer.preferred.tech/ * draw sketch and colorize it https://sketch.pixiv.net/draw * deepcolor http://color.kvfrans.com/ * gray photo to color photo http://demos.algorithmia.com/colorize-photos/ ### Image Captioning * MS https://www.captionbot.ai/ ### Visual Q&A * http://vqa.daylen.com/ * https://cloudcv.org/vqa/ ### Google's AI Experiment * Quick Draw https://quickdraw.withgoogle.com/# * Auto Draw http://www.autodraw.com/ * Sketch RNN (Draw together with a neural network) https://aiexperiments.withgoogle.com/sketch-rnn-demo ### Gaze Manipulation * http://163.172.78.19/ ### Super-Resolution * http://waifu2x.udp.jp/ ### Saliency Map * SALICON (ICCV 2015) http://salicon.net/demo/# ### Font Generation * http://fontjoy.com/ ### Image to ASCII Code * https://art.pixlab.io/ ### Image Completion * NVIDIA : https://www.nvidia.com/research/inpainting/ * http://jhyu.me/posts/2018/01/20/generative-inpainting.html ### OCR (Optical Character Recognition) * http://tesseract.projectnaptha.com/ ### Human Pose Estimation * https://control.kylemcdonald.net/posenet/ ## Others ### Neural-Net Demo * te
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