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View Code? Open in Web Editor NEWA curated list of deep learning resources for computer vision
A curated list of deep learning resources for computer vision
Hello, I wrote a tool that can validate README links (valid URLs, not duplicate). It can be run when someone submits a pull request.
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Examples
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Feel free to leave a comment ๐
Update the link for Microsoft (Deep Residual Learning) [Slide] http://research.microsoft.com/en-us/um/people/kahe/ilsvrc15/ilsvrc2015_deep_residual_learning_kaiminghe.pdf
Getting the "Missing Page" alert upon redirection to the microsoft research website.
ํฌ์์ผ deep vision ๊ด๋ จํด์ Software๋ถ๋ถ์ ๊ณต๊ฐ ์ฝ๋๋ค ์ถ๊ฐํด์ค๋?
There is some recent work on colorizing monochrome images:
Colorful Image Colorization Richard Zhang, Phillip Isola, Alexei A. Efros, ECCV 2016
https://github.com/richzhang/colorization
Ryan Dahl
http://tinyclouds.org/colorize/
I'm not sure where should this go, or if there should be a separate section for it - I can submit a PR once you let me know
์ gist -- https://gist.github.com/myungsub/c99ea6a60320d06d6812 -- ์ ์ถ๊ฐํ candidate ๋ ผ๋ฌธ list๋ง ์ ๋ฆฌํ๊ณ ์๋๋ฐ์,
๋ ผ๋ฌธ์ด ๋๋ฌด ๋ง๋ค์ใ ใ ํํธ๋ณ๋ก ๋๋ ์ ์กฐ๊ธ์ฉ ์ดํด๋ณด๋ฉด ์ข์ ๊ฒ ๊ฐ์์.
๊ทธ๋ฆฌ๊ณ ์ผ๋จ์ ๊ด๋ จ ๋ ผ๋ฌธ๋ค์ ์ ๋ถ ๋ค ์ถ๊ฐํ ๊ฑด๋ฐ ๋์ค์ ๊ฐ์๊ฐ ๋๋ฌด ๋ง์์ง๋ฉด ๋ฆฌ์คํธ ์ค์์ ์ ๋ณํด์ ์ถ๊ฐํ๋์์ผ๋ก ๋ฐ๋์ด์ผ ํ ๊น์?
PS. ํ์ฌ [Papers] ๋ถ๋ถ์ ๋ถ์ผ๋ณ๋ก ๋๋ ์ ธ ์๋๊ฑธ ๋๋ถ๋ฅ-์๋ถ๋ฅ ์์ผ๋ก ๋๋ ๋ณด๊ณ ์กฐ๋ง๊ฐ PR๋ก ์ฌ๋ ค๋ณผ ๊ณํ์ด์์. ์ ๋ชฉ๋ณด๊ณ ๋๋๊ธฐ๋ง ํ๋๊ฑด๋ฐ๋ ์๊ฐ๋ณด๋ค ์๊ฐ์ด ์ค๋ ๊ฑธ๋ฆฌ๋ค์...
Could you add a list of papers in human pose estimation? I think this is an important topic which is useful for human activity recognition, human motion prediction and human dynamics modelling. There is also a new keypoints challenge for the human pose estimation task in MSCOCO.
Would be useful if each entry had a succinct summary of the paper and commentary from someone that has read it on why you should read it.
That would make this list a lot more useful.
stereo matching CVPR 2015
visual tracking ICML 2015
Hey guys. Just to let you know you have a broken link here.
Keep up the good work.
C-Shopping-RN APP
This is a complete App developed by React Native (Expo). It is a beautiful e-commerce shopping application.
App open source address: https://github.com/huanghanzhilian/c-shopping-rn
Full stack open source address: https://github.com/huanghanzhilian/c-shopping
It feels like given the amount of existent resources, a lot of them with very high quality, the content should be restructured so it's easier to find what we need, or some kind of tool should be put in place.
A few ideas include:
Having each of the subsections as a separate file and the main README.md just linking there.
On each of the subsections add some additional layers.
For example
Perhaps topic and then year would be enough, there probably wouldn't be that many papers on a particular topic at a given conference.
Computer Vision Development Container:
https://github.com/joehoeller/NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV
Start from BoxSup
Hello, we are Korean university students. This project is an area we are interested in, so we would like to contribute.
We want to contribute through the Korean translation of the project. Is it okay to contribute?
If you're still looking for a maintainer, I might be up for giving a hand. I'm currently looking into loads of papers, I might as well share them, and I guess it could also help me structure my own stuff well :)
L0CV is a new generation of computer vision open source online learning media, a cross-platform interactive learning framework integrating graphics, source code and HTML. the L0CV ecosystem โ Notebook, Datasets, Source Code, and from Diving-in to Advanced โ as well as the L0CV Hub.
CRF-RNN (Zheng et al, 2015) has a website now with demo and source code:
Hey! Great work man.
If you want, you can add our blog: https://theaisummer.com/ in the corresponding section.
It would be highly appreciated.
Thanks in advance and congrats again.
N.A.
I think, subsections of Image Generation section need refinements.
There are papers which purely use CNNs and RNNs. And there are papers based on generative models - Variational Autoencoders(VAE), Generative Adverserial Networks(GAN), Deep Autoregressive Networks(DARN) etc. Some recent works also present techniques of mixing these works (like VAE+GAN http://arxiv.org/abs/1511.05644).
It would be better to have fine subcategories.
I can work on it if it is seems fine.
No updates in the past ~5 months despite several pending pull requests. Is this collection still being maintained?
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.