Home
Search results “Style transfer online”
coherent online style transfer yt
 
03:01
Coherent Online Style Transfer
Views: 1013 chen dongdong
How to Do Style Transfer with Tensorflow (LIVE)
 
01:06:26
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
Views: 24311 Siraj Raval
Full Online Workshop | How Deep Dream and neural style transfer work
 
01:16:52
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: 740 deepsense_ai
Style Transfer and Deep Dream: Making Art with AI
 
06:50
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: 11883 The Thought Emporium
Online Workshop | How Deep Dream and neural style transfer work
 
01:19
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: 1055 deepsense_ai
Style Transfer for Video
 
00:35
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: 2693 Nader Chehab
BDO Remastered Style Transfer
 
11:54
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: 244 Fox Nemhauser
AdaIN Style transfer - Labokube - Brussels - Belgium
 
00:23
Real-time style transfer from a live Android phone. Using AdaIN style, presented @ Digital Art Jam Labokube - Belkium #2 - 16/04/2017
Views: 142 Yann-Aël Le Borgne
Artistic style transfer for videos
 
01:15
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: 174825 Computer Vision Freiburg
style transfer
 
00:32
Views: 16 hojin12312
Style Transfer AI process
 
00:49
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: 295 Happy Finish
Portrait of Hunter using Deep Learning and Style Transfer
 
00:32
Portrait of Hunter using Deep Learning and Style Transfer
Views: 77 Pindar Van Arman
Neural Style Transfer Demo
 
00:57
The style of the original painting is learned by neural network and captured image is redrawn by this style.
Views: 55 Walid Ahmed
Real-time Neural Style Transfer for Videos
 
02:08
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: 1195 Haozhi Huang
Game of Throne Style Transfer (Muse to Scream)
 
00:12
This is a 275 frame video that starts in the style of Picasso's Muse, then gradually transitioned into the style of Munch's Scream.
Views: 159 YAO WU
PR-007:  Deep Photo Style Transfer
 
36:40
발표자료 : http://www.modulabs.co.kr/DeepLAB_library/13532 논문링크 : https://arxiv.org/abs/1703.07511
Views: 3325 Sung Kim
Style Transfer
 
01:50
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: 204 Microsoft Developer
Generate art with Deep learning using Tensorflow | Neural style transfer
 
21:20
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: 828 AI Journal
Style Transfer for Video
 
01:49
Transform video into artwork using deep learning. GitHub: https://github.com/WojciechMormul/style-transfer
Views: 337 Wojciech Mormul
Artistic Style Transfer
 
03:24
Transform arbitrary photograph into artwork using deep learning. GitHub: https://github.com/WojciechMormul/style-transfer
Views: 1621 Wojciech Mormul
stereoscopic style transfer cvpr2018
 
02:19
Stereoscopic style transfer supplementary material for cvpr2018
Views: 434 chen dongdong
This Painter AI Fools Art Historians 39% of the Time
 
02:50
Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers Crypto and PayPal links are available below. Thank you very much for your generous support! Bitcoin: 13hhmJnLEzwXgmgJN7RB6bWVdT7WkrFAHh PayPal: https://www.paypal.me/TwoMinutePapers Ethereum: 0x002BB163DfE89B7aD0712846F1a1E53ba6136b5A LTC: LM8AUh5bGcNgzq6HaV1jeaJrFvmKxxgiXg The paper "A Style-Aware Content Loss for Real-time HD Style Transfer" is available here: https://compvis.github.io/adaptive-style-transfer/ We would like to thank our generous Patreon supporters who make Two Minute Papers possible: 313V, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Brian Gilman, Christian Ahlin, Christoph Jadanowski, Dennis Abts, Emmanuel, Eric Haddad, Eric Martel, Esa Turkulainen, Evan Breznyik, Geronimo Moralez, John De Witt, Kjartan Olason, Lorin Atzberger, Marten Rauschenberg, Michael Albrecht, Michael Jensen, Milan Lajtoš, Morten Punnerud Engelstad, Nader Shakerin, Owen Skarpness, Raul Araújo da Silva, Rob Rowe, Robin Graham, Ryan Monsurate, Shawn Azman, Steef, Steve Messina, Sunil Kim, Thomas Krcmar, Torsten Reil, Zach Boldyga. https://www.patreon.com/TwoMinutePapers Thumbnail background image credit: https://pixabay.com/photo-1478831/ 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: 31250 Two Minute Papers
Neural Style Transfer by Ambroise Laurent
 
14:36
Abstract: Take a dive in the world of deep learning as it applies to art and images - We will be looking at neural style transfer, a deep learning technique to create artistic imagery by separating and combining the style and content of images. In this talk you will see neural nets demystified, the history behind the networks we have today and learn a few tips that you can apply to your own deep learning projects. We will also cover the challenges facing visual tasks and what different companies are experimenting with. Bio: I am a developer at Theodo, a London / Paris based startup that helps large corporates and startups alike, solve complex business problems through cutting edge digital solutions. An interest for technology and coding has pushed me to pick up deep learning as a hobby and I look forward to sharing with you, the insights I have gathered in my personal projects and elsewhere. Slides from the talk can be viewed here: https://slides.com/ambroiselaurent-1/deck-1#/
Views: 154 H2O.ai
artistic style transfer project demo
 
02:59
This is a demo video for artistic style transfer project.
Views: 35 HF S
Implementing Neural Style Transfer CS 299 Capstone Project by Tahsin Mayeesha
 
07:21
Imaxe is a Prisma like neural style transfer app that's going to create novel paintings in bangladeshi traditional painting style with deep learning techniques(e.g fast style transfer). The goal is to give more visibility to local art and traditions from non-western cultures as general neural style transfer apps tend to focus on the classic western paintings. The team members are : 1. Tahsin Mayeesha (Machine Learning + backend engineer) 2. Ahraf Sharif. (UI Designer and Media handler) 3. Hashmir Rahsan Toron (Software Developer) This video is created for CS299 Junior Capstone Project in North South University.
Views: 210 Tahsin Mayeesha
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
 
09:55
ICCV17 | 180 | Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization Xun Huang (Cornell), Serge Belongie () Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer. However, their framework requires a slow iterative optimization process, which limits its practical application. Fast approximations with feed-forward neural networks have been proposed to speed up neural style transfer. Unfortunately, the speed improvement comes at a cost: the network is usually tied to a fixed set of styles and cannot adapt to arbitrary new styles. In this paper, we present a simple yet effective approach that for the first time enables arbitrary style transfer in real-time. At the heart of our method is a novel adaptive instance normalization (AdaIN) layer that aligns the mean and variance of the content features with those of the style features. Our method achieves speed comparable to the fastest existing approach, without the restriction to a pre-defined set of styles. In addition, our approach allows flexible user controls such as content-style trade-off, style interpolation, color & spatial controls, all using a single feed-forward neural network.
Neural Net - Fast Style Transfer WebCam
 
01:10
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: 1410 btscheung
Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration
 
00:49
Video demo for the accepted CVPR 2018 paper -- "Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration"
Views: 287 Lu Sheng
Style transfer (with audio)
 
00:09
Same as the other one, only I figured out how to pull the audio across
Views: 257 KillinSpoon
How To Download and Transfer MIDI & Style Files
 
04:15
This video will guide you through the process of downloading and transferring files to your keyboard.
Views: 500607 Yamaha Musicsoft
Style Transfer - Polish Monarchs
 
03:21
Transform polish monarch drawing into artwork using deep learning. GitHub: https://github.com/WojciechMormul/style-transfer
Views: 95 Wojciech Mormul
The Neural Aesthetic @ ITP-NYU :: 05 Visualization, deepdream, style & texture synthesis
 
01:04:00
The Neural Aesthetic @ ITP-NYU, Fall 2018 Lecture 5 - Visualization, deepdream, style & texture synthesis 16 Oct 2018 Accompanying notes: http://ml4a.github.io/classes/itp-F18/05 Full course syllabus: http://ml4a.github.io/classes/itp-F18/ 0:00 Plan for rest of the term 7:02 A review of representation learning 12:46 Visualizing convnet features 21:38 Activating features via pixel optimization 27:47 Inceptionism & Deepdream 38:52 Masking deepdreams 46:20 Style transfer 57:13 Texture synthesis 59:41 Miscellaneous optimization-based work
Views: 314 Gene Kogan
Style Transfer in Keras (Part 2)
 
11:25
This is part 2 in a tutorial that walks you through the neural style transfer algorithm in Keras. If you have any feedback or questions, let me know! If you find some cool addition/fix/change to my code, let me know! Part 1: https://www.youtube.com/watch?v=pvjkwmRyFeo Here is a link to the full code: https://github.com/hunter-heidenreich/ML-Open-Source-Implementations/tree/master/Style-Transfer Here is a link to the python notebook: https://github.com/hunter-heidenreich/ML-Open-Source-Implementations/blob/master/Style-Transfer/Style%20Transfer.ipynb This tutorial, but on my website: http://hunterheidenreich.com/ML/style_transfer_tutorial.html Website: https://hunterheidenreich.com Twitter: https://twitter.com/hunter_heiden
Views: 207 Hunter Heidenreich
Дмитрий Ульянов: Image Style Transfer, Neural Doodles & Texture Synthesis
 
01:08:33
http://sites.skoltech.ru/compvision/members/dmitry-ulyanov/ http://ml-mipt.github.io
DeepStyleCam: A Real-time Multi-Style Transfer App on iOS
 
01:29
In this movie, we would like to present a real-time neural multi-style transfer app running on iPhone7 without any external servers. It can change photo styles by mixing 13 art styles such as Gogh and Picasso with arbitrary weights in the real-time way. This is completely different from the existing apps such as Prisma.
Views: 983 tanno0116
Delete my photos - style transfer movie preview
 
01:22
A few artistically styled scenes from the upcoming movie "Delete my photos" https://youtu.be/jLBcoymZiuE
Views: 1237 Bogdan Boyko
Animatic Style Transfer for "Paris, you got me!"
 
00:36
Students of the Technical Director (td.animationsinstitut.de) course at Filmakademie are experimenting with the latest machine learning approaches for style transfer to find applications in filmmaking. Mahmoud Hesham has successfully enhanced an animatic sequence with a reference style image for the project “Paris, you got me”, a final year project by Julie Böhm and Aleksandra Todorovic due in early 2018. This allowed a much more comprehensive vision of the final appearance at a very early stage. The results was created by applying the Fast Style Transfer implementation of Logan Engstrom: https://github.com/lengstrom/fast-style-transfer
Views: 129 R&D_Filmakademie
Rotoscoping Before Sunrise with Neural Style Transfer
 
02:02
Edit: The video res is pretty low due to low bitrate. I'll fix that later. Before Sunrise is one of my favorite films. And ever since I saw Linklater's Waking Life, I've always wanted to know what the "booth scene" would've looked like rotoscoped. Thanks to a technique called neural style transfer, I managed to do just that. I decided to code it up myself and selected the desired style after several days of trial and error. It probably would've been faster to just use one of the many existing github repos on style transfer. But it felt right creating this video from scratch by myself :)
Views: 777 Rui Shu
Transfusion Plugin for After Effects Tutorial Overview
 
38:25
In this video we take the new After Effects plugin Transfusion for a test drive. Transfusion brings Style Transfer processing to motion in After Effects for the first time. We dive into the tool to see how it can applied and adjusted for motion graphics and footage to achieve results that can't be obtained in any other way. Visit www.sideshowfx.net for more videos and subscribe!
Views: 1328 SideshowFX
Pulse of Life  - Artistic Style Transfer Version
 
01:08
Students of the Technical Director (td.animationsinstitut.de) course at Filmakademie are experimenting with the latest machine learning approaches for style transfer to find applications in filmmaking. Juraj Tomori, applied an alternate style to the AniTrailer/AniPlay production “Pulse of Life” (original production and credits can be found on: https://www.youtube.com/watch?v=Wb6m68pRs_4). While the initial visual identity was realistic he experimented with a rather abstract representation. Juraj also documented his approach and published a tutorial on how to achieve the result at: https://goo.gl/V1EPoS The results was created by applying the Fast Style Transfer implementation of Logan Engstrom: https://github.com/lengstrom/fast-style-transfer
Views: 190 R&D_Filmakademie

Pregnancy loss australia newsletter formats
Vedanta newsletter formats
The cube 2012 application letters
Sample cover letter for mortgage application
Writing resume service