MeInGame: Create a Game Character Face from a Single Portrait
Github : https://github.com/FuxiCV/MeInGame
Paper: https://arxiv.org/abs/2102.02371v1
Demo: https://www.youtube.com/watch?v=597cvKOegfE&feature=youtu.be&ab_channel=EdwardLin
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Github : https://github.com/FuxiCV/MeInGame
Paper: https://arxiv.org/abs/2102.02371v1
Demo: https://www.youtube.com/watch?v=597cvKOegfE&feature=youtu.be&ab_channel=EdwardLin
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❤1
🎨 Colorization Transformer by Google
💻 Github: https://github.com/google-research/google-research/tree/master/coltran
📝 Paper: https://arxiv.org/abs/2102.04432v1
🌐 Pre-trained model: https://console.cloud.google.com/storage/browser/gresearch/coltran;tab=objects?pli=1&prefix=&forceOnObjectsSortingFiltering=false
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💻 Github: https://github.com/google-research/google-research/tree/master/coltran
📝 Paper: https://arxiv.org/abs/2102.04432v1
🌐 Pre-trained model: https://console.cloud.google.com/storage/browser/gresearch/coltran;tab=objects?pli=1&prefix=&forceOnObjectsSortingFiltering=false
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🔊 Deep Perceptual Audio Metric (DPAM)
Github : https://github.com/pranaymanocha/PerceptualAudio
Paper: https://arxiv.org/abs/2102.05109v1
Website: https://pixl.cs.princeton.edu/pubs/Manocha_2021_CCL/index.php
Video: https://www.youtube.com/watch?v=yOceeut_4Gg&ab_channel=PranayManocha
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Github : https://github.com/pranaymanocha/PerceptualAudio
Paper: https://arxiv.org/abs/2102.05109v1
Website: https://pixl.cs.princeton.edu/pubs/Manocha_2021_CCL/index.php
Video: https://www.youtube.com/watch?v=yOceeut_4Gg&ab_channel=PranayManocha
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🚀 High-Performance Large-Scale Image Recognition Without Normalization
Github: https://github.com/deepmind/deepmind-research/tree/master/nfnets
Paper: https://arxiv.org/abs/2102.06171v1
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Github: https://github.com/deepmind/deepmind-research/tree/master/nfnets
Paper: https://arxiv.org/abs/2102.06171v1
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GitHub
deepmind-research/nfnets at master · google-deepmind/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications - google-deepmind/deepmind-research
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🧪 Alchemy: A structured task distribution for meta-reinforcement learning
Deepmind: https://deepmind.com/research/publications/alchemy
Github: https://github.com/deepmind/dm_alchemy
Paper: https://arxiv.org/abs/2102.02926
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Deepmind: https://deepmind.com/research/publications/alchemy
Github: https://github.com/deepmind/dm_alchemy
Paper: https://arxiv.org/abs/2102.02926
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👁 18 All-Time Classic Open Source Computer Vision Projects for Beginners
https://www.analyticsvidhya.com/blog/2020/09/18-open-source-computer-vision-projects-beginners/
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https://www.analyticsvidhya.com/blog/2020/09/18-open-source-computer-vision-projects-beginners/
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👍1
💪 These Neural Networks Have Superpowers!
Github: https://github.com/CompVis/taming-transformers
Taming Transformers for High-Resolution Image Synthesis: https://compvis.github.io/taming-transformers/
Paper: https://arxiv.org/abs/2012.09841
Video: https://www.youtube.com/watch?v=o7dqGcLDf0A&ab_channel=TwoMinutePapers
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Github: https://github.com/CompVis/taming-transformers
Taming Transformers for High-Resolution Image Synthesis: https://compvis.github.io/taming-transformers/
Paper: https://arxiv.org/abs/2012.09841
Video: https://www.youtube.com/watch?v=o7dqGcLDf0A&ab_channel=TwoMinutePapers
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📍TransGAN: Two Transformers Can Make One Strong GAN
Github: https://github.com/VITA-Group/TransGAN
Paper: https://arxiv.org/abs/2102.07074
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Github: https://github.com/VITA-Group/TransGAN
Paper: https://arxiv.org/abs/2102.07074
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👍1
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🕹 Mastering Atari with Discrete World Models
Github: https://github.com/danijar/dreamerv2
Google research: https://ai.googleblog.com/2021/02/mastering-atari-with-discrete-world.html
Paper: https://arxiv.org/abs/2010.02193
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Github: https://github.com/danijar/dreamerv2
Google research: https://ai.googleblog.com/2021/02/mastering-atari-with-discrete-world.html
Paper: https://arxiv.org/abs/2010.02193
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Unbiased Teacher for Semi-Supervised Object Detection
Github: https://github.com/facebookresearch/unbiased-teacher
Paper: https://arxiv.org/abs/2102.09480
Project: https://ycliu93.github.io/projects/unbiasedteacher.html
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Github: https://github.com/facebookresearch/unbiased-teacher
Paper: https://arxiv.org/abs/2102.09480
Project: https://ycliu93.github.io/projects/unbiasedteacher.html
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🔥 Model Search by Google
Automatically build and deploy state-of-the-art machine learning models on structured data.
Github: https://github.com/google/model_search
Paper: https://pdfs.semanticscholar.org/1bca/d4cdfbc01fbb60a815660d034e561843d67a.pdf
Project: https://cloud.google.com/automl-tables
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Automatically build and deploy state-of-the-art machine learning models on structured data.
Github: https://github.com/google/model_search
Paper: https://pdfs.semanticscholar.org/1bca/d4cdfbc01fbb60a815660d034e561843d67a.pdf
Project: https://cloud.google.com/automl-tables
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🚀 DALL-E Zero-Shot Text-to-Image Generation
Github: https://github.com/openai/DALL-E
Paper: https://arxiv.org/abs/2102.12092
OpenAi: https://openai.com/blog/dall-e/
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Github: https://github.com/openai/DALL-E
Paper: https://arxiv.org/abs/2102.12092
OpenAi: https://openai.com/blog/dall-e/
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GitHub
GitHub - openai/DALL-E: PyTorch package for the discrete VAE used for DALL·E.
PyTorch package for the discrete VAE used for DALL·E. - openai/DALL-E
When Attention Meets Fast Recurrence: Training Language Models with Reduced Compute
Github: https://github.com/asappresearch/sru
Paper: https://arxiv.org/abs/2102.12459v1
Project: https://www.asapp.com/blog/reducing-the-high-cost-of-training-nlp-models-with-sru/
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Github: https://github.com/asappresearch/sru
Paper: https://arxiv.org/abs/2102.12459v1
Project: https://www.asapp.com/blog/reducing-the-high-cost-of-training-nlp-models-with-sru/
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GitHub
GitHub - asappresearch/sru: Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755) - asappresearch/sru
XLA: Optimizing Compiler for Machine Learning
Tensorflow: https://www.tensorflow.org/xla
XLA Architecture: https://www.tensorflow.org/xla/architecture
Github: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla
Code: https://www.tensorflow.org/xla/tutorials/jit_compile
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Tensorflow: https://www.tensorflow.org/xla
XLA Architecture: https://www.tensorflow.org/xla/architecture
Github: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla
Code: https://www.tensorflow.org/xla/tutorials/jit_compile
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⭐ CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations
Github: https://github.com/Davidzhangyuanhan/CelebA-Spoof
Paper: https://arxiv.org/abs/2102.12642v2
Dataset: https://drive.google.com/drive/folders/1OW_1bawO79pRqdVEVmBzp8HSxdSwln_Z
Video: https://www.youtube.com/watch?v=A7XjSg5srvI&t=4s&ab_channel=YuanhanZhang
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Github: https://github.com/Davidzhangyuanhan/CelebA-Spoof
Paper: https://arxiv.org/abs/2102.12642v2
Dataset: https://drive.google.com/drive/folders/1OW_1bawO79pRqdVEVmBzp8HSxdSwln_Z
Video: https://www.youtube.com/watch?v=A7XjSg5srvI&t=4s&ab_channel=YuanhanZhang
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🔥1
CogDL: An Extensive Research Toolkit for Deep Learning on Graphs
http://keg.cs.tsinghua.edu.cn/cogdl/
Github: https://github.com/THUDM/cogdl
Paper: https://arxiv.org/abs/2103.00959
Dateset: https://github.com/THUDM/cogdl/blob/master/cogdl/datasets/README.md
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http://keg.cs.tsinghua.edu.cn/cogdl/
Github: https://github.com/THUDM/cogdl
Paper: https://arxiv.org/abs/2103.00959
Dateset: https://github.com/THUDM/cogdl/blob/master/cogdl/datasets/README.md
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🤖 A Text-to-Speech Transformer in TensorFlow 2
Github: https://github.com/as-ideas/TransformerTTS
Paper: https://arxiv.org/abs/2103.00993v1
Samples: https://as-ideas.github.io/TransformerTTS/
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Github: https://github.com/as-ideas/TransformerTTS
Paper: https://arxiv.org/abs/2103.00993v1
Samples: https://as-ideas.github.io/TransformerTTS/
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🧠 Multimodal Neurons in Artificial Neural Networks
https://openai.com/blog/multimodal-neurons/
Github: https://github.com/openai/CLIP-featurevis
Paper: https://distill.pub/2021/multimodal-neurons/
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https://openai.com/blog/multimodal-neurons/
Github: https://github.com/openai/CLIP-featurevis
Paper: https://distill.pub/2021/multimodal-neurons/
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Openai
Multimodal neurons in artificial neural networks
We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding…
Register for the International Data Analysis Olympiad (IDAO-2021)! The registration continues until March 12.
This year, HSE Faculty of Computer Science and Yandex are holding the Olympiad for the fourth time. This year's Platinum Partner is ‘Otkritie’ Bank. The Olympiad is organised by leading data analysts for their future colleagues, early career analysts and scientists.
The online tour will focus on the search for dark matter - one of the few remaining mysteries of fundamental physics. Dark matter cannot be seen because it does not interact with light and interacts very weakly with ordinary matter. The task of IDAO participants is to build a model that recognises some known observation processes, so that they can be excluded from the search for dark matter.
Details and registration https://idao.world
This year, HSE Faculty of Computer Science and Yandex are holding the Olympiad for the fourth time. This year's Platinum Partner is ‘Otkritie’ Bank. The Olympiad is organised by leading data analysts for their future colleagues, early career analysts and scientists.
The online tour will focus on the search for dark matter - one of the few remaining mysteries of fundamental physics. Dark matter cannot be seen because it does not interact with light and interacts very weakly with ordinary matter. The task of IDAO participants is to build a model that recognises some known observation processes, so that they can be excluded from the search for dark matter.
Details and registration https://idao.world
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Anycost GAN
Anycost GANs for Interactive Image Synthesis and Editing
https://hanlab.mit.edu/projects/anycost-gan/
Github: https://github.com/mit-han-lab/anycost-gan
Paper: https://arxiv.org/abs/2103.03243
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Anycost GANs for Interactive Image Synthesis and Editing
https://hanlab.mit.edu/projects/anycost-gan/
Github: https://github.com/mit-han-lab/anycost-gan
Paper: https://arxiv.org/abs/2103.03243
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