Search results “Style transfer online”
coherent online style transfer yt
Coherent Online Style Transfer
Views: 1245 chen dongdong
Style Transfer and Deep Dream: Making Art with AI
Everywhere you look nowadays you find AI. From filters on snap chat, tools in photoshop, the ads next to videos and even the video suggestions next to this video. Two such AI programs allow you to make amazing AI art and bend reality in weird ways. Style transfer allows you to take the style from one image, like Van Gogh's Starry Night, and transfer it to a different image. This allows you to quickly generate new master pieces by your favorite artists, or give something a fresh look. There is a version of this program that works on videos too which we'll explore in the future. Deep dream on the other hand is ai turned on it's head. Instead of using the AI to classify things, we allow it to manipulate an image to fit some of the data its already learned. This produces sureal images where animals and structure get generated out of noise. All of this is done in an online tool called Deep Dream Generator: https://deepdreamgenerator.com Some further reading and references: Original Paper Style Transfer - https://arxiv.org/pdf/1508.06576.pdf Deep Dream Article - https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html Deep Dream Video by computerphile - https://www.youtube.com/watch?v=BsSmBPmPeYQ __________________________________________________________________ Interested in some sweet science themed designs for your wardrobe or wall? Click the link below to see all the great items currently being offered: https://www.redbubble.com/people/chironex?asc=u __________________________________________________________________ My Social Media Pages: Instagram: https://www.instagram.com/thethoughtemporium/ Facebook: https://www.facebook.com/thethoughtemporium/ Twitter: https://www.twitter.com/TTEchironex Website: http://thethoughtemporium.com/ __________________________________________________________________ As always, thanks to my awesome Patrons for helping to make these video possible. Special thanks to: -Al Dass -Patryk Wycech -Larry -Adam Sheppard -Michael Chatzidakis -Oliver -Justin Hendryx -Paul Emmerich -orotusso -Alex Lemna -Cataract Bumblesnatch -Jonas Abreu -Anita Fowler -Ben Davis -Guhur Alexandre -Ben Krasnow -Anatoly Bazarov -John De Witt -Terry Fuller -BioQuisitive -Morten Eriksen -Omun
Views: 17549 The Thought Emporium
How to Do Style Transfer with Tensorflow (LIVE)
We're going to learn about all the details of style transfer (especially the math) using just Tensorflow. The goal of this session is for you to understand the details behind how style+content loss is calculated and minimized. We'll also talk about future discoveries. Code for this video: https://github.com/llSourcell/How_to_do_style_transfer_in_tensorflow Learning resources: http://www.makeuseof.com/tag/create-neural-paintings-deepstyle-ubuntu/ https://blog.paperspace.com/art-with-neural-networks/ https://www.tensorflow.org/versions/r0.11/how_tos/ https://no2147483647.wordpress.com/2015/12/21/deep-learning-for-hackers-with-mxnet-2/ https://code.facebook.com/posts/196146247499076/delivering-real-time-ai-in-the-palm-of-your-hand/ http://kawahara.ca/deep-dreams-and-a-neural-algorithm-of-artistic-style-slides-and-explanations/ http://www.chioka.in/tensorflow-implementation-neural-algorithm-of-artistic-style Please subscribe! And like. And comment. That's what keeps me goin And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 26869 Siraj Raval
Artistic Style Transfer
This is a demo video for our paper: Balancing Content and Style with Two-Stream FCNs for Style Transfer Conference: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) Link: https://ieeexplore.ieee.org/document/8354256/ Source video: https://www.youtube.com/watch?v=j9jqI5dJH5I
Views: 20 Đức Võ Minh
style transfer demo 01
Views: 232 Bogdan Boyko
Style Transfer for Video
This is my attempt to do style transfer for video. Style transfer is a technique of recomposing images or video in the style of other images using deep learning. The original image is "La Muse" by Picasso. For processing I used the awesome Fast Style Transfer project. Unfortunately my graphics card did not let me use a resolution higher than 720p for the input video. More info and links below. What is Style Transfer? http://genekogan.com/works/style-transfer/ Fast Style Transfer project: https://github.com/lengstrom/fast-style-transfer/ La Muse by Picasso: https://www.wikiart.org/en/pablo-picasso/a-muse-1935 Video: my iPod Music: Zero7
Views: 3063 Nader Chehab
Style Transfer
To create the style transfer application, we used Visual Studio Tools for AI to train the deep learning models and include them in our app. Visual Studio Tools for AI improved our productivity by easily enabling stepping through our Keras + Tensorflow model training code on our local dev machine, then submitting to Azure VMs with powerful Nvidia GPUs. Create a Free Account (Azure): https://aka.ms/azft-ai For more information: https://www.ailab.microsoft.com/experiments/99907c05-d487-450b-9ee9-901b40205e81
Views: 308 Microsoft Developer
Online Workshop | How Deep Dream and neural style transfer work
Projects like Deep Dream and Prisma are great examples of how simple deep learning models can be used to produce incredible results. Today, generating value using deep learning is just a question of applying it to new problems creatively. Join our online workshop on February 27th for Deep Dream and neural style transfer and learn specific techniques provided by Keras and Neptune, so you could get your hands dirty with deep learning effectively from the get-go. Sign up for our online workshop here: https://www.crowdcast.io/e/online-workshop-deep/register If you want to make the most of the workshop, please install Neptune and Keras on your environment before the event. Don’t have Neptune? Join our Early Adopter program and get the access: https://deepsense.io/neptune-early-adopter-program/ Follow our channel to stay up-to-date with our upcoming webinars and online workshops.
Views: 1104 deepsense_ai
Full Online Workshop | How Deep Dream and neural style transfer work
Deep Dream and neural style transfer - the way of matching deep learning with art. Projects like Deep Dream and Prisma are great examples of how simple deep learning models can be used to produce incredible results. In this webinar you will learn specific techniques provided by Keras and Neptune, so you could get your hands dirty with deep learning effectively from the get-go. Speaker: Jakub Czakon, Data Scientist at deepsense.io
Views: 898 deepsense_ai
A Style-Based Generator Architecture for Generative Adversarial Networks
Paper (PDF): http://stylegan.xyz/paper Authors: Tero Karras (NVIDIA) Samuli Laine (NVIDIA) Timo Aila (NVIDIA) Abstract: We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis. The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and also better disentangles the latent factors of variation. To quantify interpolation quality and disentanglement, we propose two new, automated methods that are applicable to any generator architecture. Finally, we introduce a new, highly varied and high-quality dataset of human faces.
Views: 885645 Tero Karras FI
Transfusion Tutorial
https://aescripts.com/transfusion/ Transfusion is the first plugin to bring AI Style Transfer in After Effects. It works with pre-trained neural networks to mimic various styles over your photos and videos.
Views: 5882 aescripts + aeplugins
Style Transfer for Video
Transform video into artwork using deep learning. GitHub: https://github.com/WojciechMormul/style-transfer
Views: 450 Wojciech Mormul
Style Transfer Part 2: Real-Time Style Transfer with ml5.js with Yining Shi
In this video, Yining Shi uses this trained model to style a real-time image, in browser, using ml5.js and p5.js. #ThisDotStyle #StyleTransfer #MachineLearning To sign up to Spell: https://spell.run/codingtrain 🎥 Part 1: https://youtu.be/STHRNIJc-vI This video is sponsored by Spell. 🔗 Style Transfer Example: https://yining1023.github.io/styleTransfer_spell/ 🔗 Detailed Instructions: https://github.com/yining1023/styleTransfer_spell/ 🔗 ml5.js: https://ml5js.org/ 🔗 p5.js: https://p5js.org 🔗 Fast Style Transfer in TensorFlow by Logan Engstrom: https://github.com/lengstrom/fast-style-transfer/ 🔗 Machine Learning 101: https://spell.run/docs/core_concepts/#machine-learning-101 🔗 What Neural Networks See by Gene Kogan: https://experiments.withgoogle.com/what-neural-nets-see 🔗 Fast style transfer in deeplearn.js by Reiichiro Nakano: https://github.com/reiinakano/fast-style-transfer-deeplearnjs 🎥 To learn more about style transfers: https://youtu.be/gye9hSIrRWI 🎥 Intro to Spell: https://youtu.be/ggBOAPtFjYU 🎥 Two Minute Papers: https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg Work Cited: 📙 A Neural Algorithm of Artistic Style [Leon A. Gatys, Alexander S. Ecker, Matthias Bethge] 📙 Perceptual Losses for Real-Time Style Transfer and Super-Resolution [Justin Johnson, Alexandre Alahi, Li Fei-Fei] 📙 Artistic style transfer for videos [Manuel Ruder, Alexey Dosovitskiy, Thomas Brox] 📙 Deep Photo Style Transfer [Fujun Luan, Sylvain Paris, Eli Shechtman, Kavita Bala] 📙 Visual Attribute Transfer through Deep Image Analogy [Jing Liao, Yuan Yao, Lu Yuan, Gang Hua, Sing Bing Kang] 📙 Universal Style Transfer via Feature Transforms [Yijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, Ming-Hsuan Yang] Yining Shi is an artist and researcher who is interested in building tools to craft a better learning experience for people. She is also an adjunct professor at Interactive Telecommunications Program (ITP) at NYU, where she teaches Machine Learning for the Web class. She also contributes to various open source projects like p5.js, ml5.js. She currently works at Sourcemap as a Senior Software Engineer. Yining Shi's website: http://1023.io/
Views: 7359 The Coding Train
Neural Style Transfer - Tensorflow
Check the post and the code: http://laid.delanover.com/image-style-transfer-using-convolutional-neural-networks-tensorflow-implementation/
Real-time Neural Style Transfer for Videos
A supplementary video for the paper "Real-time Neural Style Transfer for Videos" in CVPR 2017. http://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Real-Time_Neural_Style_CVPR_2017_paper.pdf
Views: 2050 Haozhi Huang
Style Transfer applied to 3D textures [Demo]
Using Machine Learning techniques, Artomatix can: - Apply the visual style of a source image to the other textures used in a project; - Apply the high-level of detail of one texture to a lower-res texture (e.g. use PBR textures obtained through photogrammetry to enhance an existing texture). Beta version of the service available now - Please reach out to [email protected] for more info!
Views: 3652 Artomatix
Artistic style transfer for videos
Style transfer for videos, as described in the paper "Artistic style transfer for videos" by Manuel Ruder, Alexey Dosovitskiy and Thomas Brox http://arxiv.org/abs/1604.08610 Another video with more examples and more technical comparisons: https://youtu.be/vQk_Sfl7kSc Code https://github.com/manuelruder/artistic-videos
Views: 184259 Computer Vision Freiburg
Stereoscopic Style Transfer AI   Art is not what you see? by Martin Förtsch, Thomas Endres
Subscribe to Devoxx on YouTube @ https://bit.ly/devoxx-youtube Like Devoxx on Facebook @ https://www.facebook.com/devoxxcom Follow Devoxx on Twitter @ https://twitter.com/devoxx What if Virtual Reality glasses could transform your environment into a three-dimensional work of art in realtime? What if every detail of the world would be shown in the style of a painting from Van Gogh? One of the many interesting developments in the field of Deep Learning is the so called "Style Transfer". It describes a possibility to create a patchwork (or pastiche) from two images. While one of these images defines the the artistic style of the result picture, the other one is used for extracting the image content. The Hardware Hacking Team from TNG Technology Consulting managed to build an application using OpenCV and Tensorflow to realize such goggles. When you see the world through these glasses, your environment will be displayed in the styles of famous painters like Claude Monet or Pablo Picasso. Within this talk you will be introduced into the scientific field of Realtime Style Transfer. It will also cover and explain in detail the Deep Learning techniques used for this application.
Views: 231 Devoxx
Style transfer (with audio)
Same as the other one, only I figured out how to pull the audio across
Views: 300 KillinSpoon
Style Transfer AI process
A look into the process behind the AI style transfer technique we used in our VR experience for the Royal Academy in collaboration with Yinka Shonibare MBE.
Views: 467 Happy Finish
How To Download and Transfer MIDI & Style Files
This video will guide you through the process of downloading and transferring files to your keyboard.
Views: 530453 Yamaha Musicsoft
Fast Neural Style Transfer for Video
Demonstration purpose for the paper Fast Neural Style Transfer for Video. Clips appear in the video are respectively Sing (2016) 2001: A Space Odyssey (1968) Minions (2015)
Views: 1141 Feng Qi
Painting Style Transfer for Head Portraits
Head portraits are popular in traditional painting. Automating portrait painting is challenging as the human visual system is sensitive to the slightest irregularities in human faces. Applying generic painting techniques often deforms facial structures. On the other hand portrait painting techniques are mainly designed for the graphite style and/or are based on image analogies; an example painting as well as its original unpainted version are required. This limits their domain of applicability. We present a new technique for transferring the painting from a head portrait onto another. Unlike previous work our technique only requires the example painting and is not restricted to a specific style. We impose novel spatial constraints by locally transferring the color distributions of the example painting. This better captures the painting texture and maintains the integrity of facial structures. We generate a solution through Convolutional Neural Networks and we present an extension to video. Here motion is exploited in a way to reduce temporal inconsistencies and the shower-door effect. Our approach transfers the painting style while maintaining the input photograph identity. In addition it significantly reduces facial deformations over state of the art. URL: http://dl.acm.org/citation.cfm?id=2925968&CFID=645113485&CFTOKEN=19098431
Views: 2656 Mohamed Elgharib
Fast Style Transfer Video - Deep learning
Fast style transfer video using processed with code from https://github.com/lengstrom/fast-style-transfer Music from https://www.youtube.com/watch?v=cNgTDl28JNM and https://www.youtube.com/watch?v=gvkh5udzKds Original video from https://www.youtube.com/watch?v=13wt6cmCRK0
Views: 3372 Tetsujinfr
Neural Net - Fast Style Transfer WebCam
Playing with Tensorflow implementation of Fast Style Transfer Neural Network code, running on Mac OSX El Capitan with Nvidia GT 750M GPU (~200 cores), generating this real-time interactive experiment. All happy. :)
Views: 1663 btscheung
fast artistic style transfer for video
fast artistic video demo
Views: 511 李俊英
BDO Remastered Style Transfer
First minute contains footage from Black Desert Online Remastered. Next clips are of that same footage but with neural network applied style transfer. You will see a painting that was used to create each section so you can compare how well the transfer was applied. Have fun! Technicalities: Footage was recorded on Nvidia GTX 770, but neural network computations were made using Nvidia GTX 1070. Training of a style model takes around 4-5 hours using CUDA with TenserFlow; generating the images for one clip takes around 15 minutes. Music from Lord of Dance. Great tunes! Buy the album to support the artists! :)
Views: 289 Fox Nemhauser
Universal Neural Style Transfer | Two Minute Papers #213
The paper "Universal Style Transfer via Feature Transforms" and its source code is available here: https://arxiv.org/abs/1705.08086 https://github.com/Yijunmaverick/UniversalStyleTransfer Recommended for you: https://www.youtube.com/watch?v=Rdpbnd0pCiI - What is an Autoencoder? We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Andrew Melnychuk, Brian Gilman, Christian Ahlin, Christoph Jadanowski, Dave Rushton-Smith, Dennis Abts, Eric Haddad, Esa Turkulainen, Evan Breznyik, Kaben Gabriel Nanlohy, Malek Cellier, Marten Rauschenberg, Michael Albrecht, Michael Jensen, Michael Orenstein, Raul Araújo da Silva, Robin Graham, Steef, Steve Messina, Sunil Kim, Torsten Reil. https://www.patreon.com/TwoMinutePapers One-time payments: PayPal: https://www.paypal.me/TwoMinutePapers Bitcoin: 13hhmJnLEzwXgmgJN7RB6bWVdT7WkrFAHh Music: Antarctica by Audionautix is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) Artist: http://audionautix.com/ Thumbnail background image credit: https://pixabay.com/photo-1978682/ Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Facebook: https://www.facebook.com/TwoMinutePapers/ Twitter: https://twitter.com/karoly_zsolnai Web: https://cg.tuwien.ac.at/~zsolnai/
Views: 27859 Two Minute Papers
Kauf | When You're Out | // Neural Artistic Style Transfer v.4 \\
Kauf | When You're Out | Neural Artistic Style Transfer v.4 Made famous by Radio Mirror Park. Sources: https://vimeo.com/280539413 https://vimeo.com/175540110 https://vimeo.com/174287495 https://vimeo.com/280753619
Generate art with Deep learning using Tensorflow | Neural style transfer
In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery. Reserach paper: https://arxiv.org/abs/1508.06576 Utils file: https://gist.github.com/aijournal/f01caef7c04f138c340ca8af06f4bdf4 Pretrained model (VGG 19): http://www.vlfeat.org/matconvnet/models/imagenet-vgg-verydeep-19.mat Please support me on Patreon : https://patreon.com/aijournal
Views: 1451 AI Journal
Generative NN: Style Transfer - TensorFlow and Deep Learning Singapore
Speaker: Martin Andrews Event Page: https://www.meetup.com/TensorFlow-and-Deep-Learning-Singapore/events/238584480/ Produced by Engineers.SG
Views: 1074 Engineers.SG
Digging into style transfer
As a part of a Udacity deep learning course I'm talking about style transfer and showing what information can we extract from various layers. https://blog.udacity.com/2018/10/introducing-the-pytorch-scholarship-challenge-from-facebook.html The notebook with all the code is here: https://github.com/slawekslex/dl_experiments/blob/master/pytorch_challenge/Webinar.ipynb
Views: 62 Sławek Biel
[Original Style Transfer] A Neural Algorithm of Artistic Style | TDLS Foundational
Toronto Deep Learning Series - Fast Track Stream https://tdls.a-i.science/events/2019-03-14 A Neural Algorithm of Artistic Style "In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery."
Delete my photos - style transfer movie preview
A few artistically styled scenes from the upcoming movie "Delete my photos" https://youtu.be/jLBcoymZiuE
Views: 1268 Bogdan Boyko
AI Driven Style Transfer comes to Autodesk University 2017
Brian Piccioni, Sr. Director of Marketing at NVIDIA, shows how a simple sketch can turn into a work of art through the power of AI at Autodesk University 2017.
Views: 995 NVIDIA
Artistic Video Style Transfer.
Style transfer implementation on a 5 second video of a bird shaking its head. Github implementation: https://github.com/manuelruder/artistic-videos
Views: 102 Dylan Ler
Portrait of Hunter using Deep Learning and Style Transfer
Portrait of Hunter using Deep Learning and Style Transfer
Views: 82 Pindar Van Arman
Style Transfer for Headshot Portraits
[Recommended resolution: 1080p] To appear in SIGGRAPH 2014. Abstract: Headshot portraits are a popular subject in photography but to achieve a compelling visual style requires advanced skills that a casual photographer will not have. Further, algorithms that automate or assist the stylization of generic photographs do not perform well on headshots due to the feature-specific, local retouching that a professional photographer typically applies to generate such portraits. We introduce a technique to transfer the style of an example headshot photo onto a new one. This can allow one to easily reproduce the look of renowned artists. At the core of our approach is a new multiscale technique to robustly transfer the local statistics of an example portrait onto a new one. This technique matches properties such as the local contrast and the overall lighting direction while being tolerant to the unavoidable differences between the faces of two different people. Additionally, because artists sometimes produce entire headshot collections in a common style, we show how to automatically find a good example to use as a reference for a given portrait, enabling style transfer without the user having to search for a suitable example for each input. We demonstrate our approach on data taken in a controlled environment as well as on a large set of photos downloaded from the Internet. We show that we can successfully handle styles by a variety of different artists.
Views: 46087 yichang shih
Real-Time Style Transfer
Views: 61 Alphamoon
Zootopia in Artistic Style
Video looks awesome in artistic style! In this video you'll find following styles: sketch, water color, Chinese water color, stars (cinematic effect), fire (cinematic effect), snow, color sketch, the matrix (cinematic effect), Van Gogh, news paper, cartoon. This video clip is rendered by the Deep Black Engine in realtime. Deep Black Engine is an deep-learning -based style transfer algorithm. All artistic style is available and free in the Deep Black app in iOS & Android App Stores. Convert your own video and photo in to art! Deep Black team: www.deepblack-ai.com
Views: 199 Deep Black
Simon Colton — ML-based Style Transfer for Game Assets (ASYNC Oct '17)
Simon Colton is Professor at the MetaMakers Institute, Falmouth University, and at the Computational Creativity Group, Goldsmiths, University of London. Here he talks about his first thoughts on and first experiments with ML-based style transfer for game assets, in the context of the long-running Painting Fool project. This talk is part of the October 2017 edition of ASYNC, an online conference run by The MetaMakers Institute at Falmouth University, UK: http://metamakersinstitute.com/events/async/
Views: 142 ThoseMetaMakers
Euphonie Intro - Rave Sickness (Neural style transfer 4k)
Track #1 Album Euphonie https://ravesickness.bandcamp.com/album/euphonie https://soundcloud.com/ravesickness Video made using convolutional deep neural network : https://github.com/yusuketomoto/chainer-fast-neuralstyle
Views: 856 dorni
Building an AI model for style transfer using U-Net CNN : Part 1 GPU
In this video , we'll build a convolutional network, to try and understand how they work by generating images that maximize the activation of the filters in the convolutional layers. To generate these images, we apply gradient ascent to the inputs (which will be images with random noise Follow me on Instagram - https://www.instagram.com/siddharthac... Pleases LIKE, SHARE and SUSCRIBE . If you have any doubt pleases let me know in the comments My game " Killer Box"" https://killer-box.en.uptodown.com/android/download My Laptop Specs: Laptop : Lenovo Legion Y520 R.A.M: 32 GB Graphics Card: GTX 1050ti (4GB) Hard Disk: 2TB
Views: 200 AI with Siddhartha
Tech Showcase: Deep Artistic Style Transfer: From Images to Videos
This demo demonstrates several applications of Microsoft’s recent work in artistic style transfer for images and videos. One technology, called StyleBank, provides an explicit representation for visual styles with a feedforward deep network that can clearly separate the content and style from an image. This framework can render stylized videos online, achieving more stable rendering results than in the past. In addition, the Deep Image Analogy technique takes a pair of images, transferring the visual attributes from one to the other. It enables a wide variety of applications in artistic effects. See more on this video at https://www.microsoft.com/en-us/research/event/faculty-summit-2017/
Views: 750 Microsoft Research
Neural Style Transfer Demo
The style of the original painting is learned by neural network and captured image is redrawn by this style.
Views: 84 Walid Ahmed

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