Data Science by ODS.ai 🦜
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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @haarrp
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​​GSCNN: video segmetation architecture

Semantic segmentation GSCNN significantly outperforms DeepLabV3+ on Cityscapes benchmark.

Paper: https://arxiv.org/abs/1907.05740
Github (Project): https://github.com/nv-tlabs/GSCNN

#DL #CV #NVidiaAI #Nvidia #autonomous #selfdriving #car #RL #segmentation
​​πŸ”₯Interactive demo of GAN turning doodles into beautiful pictures

NVidia released #GauGAN for anyone to use. Trained on 1M images, the #GAN tool automatically turns doodles into photorealistic landscapes.

Project page: https://www.nvidia.com/en-us/research/ai-playground/
Interactive demo: http://nvidia-research-mingyuliu.com/gaugan

#Nvidia #CV #DL
​​mellotron by #NVIDIA

It's a multispeaker #voice synthesis model based on #Tacotron 2 GST that can make a voice emote and sing without emotive or singing training data.

By explicitly conditioning on rhythm and continuous pitch contours from an audio signal or music score, Mellotron is able to generate #speech in a variety of styles ranging from reading speech to expressive speech, from slow drawls to rap and from monotonous voice to singing voice.

Unlike other methods, Mellotron trains using only read speech data without alignments between text and audio.

Site: https://nv-adlr.github.io/Mellotron
Paper: https://arxiv.org/abs/1910.11997
Git: https://github.com/NVIDIA/mellotron
​​An autonomous AI racecar using NVIDIA Jetson Nano

Usually DS means some blue collar work. Rare cases suggest physical interactions. This set by #NVidia allows to build $400/$600 toy car capable of #selfdriving.

#JetRacer comes with a couple examples to get you up and running. The examples are in the format of Jupyter Notebooks, which are interactive documents which combine text, code, and visualization. Once you've completed the notebooks, start tweaking them to create your own racing software!

Github: https://github.com/NVIDIA-AI-IOT/jetracer

#autonomousvehicle #rl #jupyter #physical
​​OpenCV β€˜dnn’ with NVIDIA GPUs: 1.549% faster YOLO, SSD, and Mask R-CNN

- Object detection and segmentation
- Working Python implementations of each
- Includes pre-trained models

tutorial: https://t.co/Wt0IrJObcE?amp=1

#OpenCV #dl #nvidia
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Nvidia AI Noise Reduction

#Nvidia launches #KrispAI competitor Noise Reduction by AI on RTX Videocards.

Seems it works significantly better then other that kind of tools. But it needs to have Nvidia RTX officially.

But it possible to run it on older cards. The instruction is below. Or you can just download already hacked executable (also, below)

Setup Guide: https://www.nvidia.com/en-us/geforce/guides/nvidia-rtx-voice-setup-guide/
The instruction: https://forums.guru3d.com/threads/nvidia-rtx-voice-works-without-rtx-gpu-heres-how.431781/
Executable (use it on your own risk): https://mega.nz/file/CJ0xDYTB#LPorY_aPVqVKfHqWVV7zxK8fNfRmxt6iw6KdkHodz1M

#noisereduction #soundlearning #dl #noise #sound #speech #nvidia
​​Learning to Simulate Dynamic Environments with GameGAN

#Nvidia designed a GAN that able to recreate games without any game engine. To train it, authors of the model use experience collected by reinforcement learning and other techniques.

GameGAN successfully reconstructed all mechanics of #Pacman game. Moreover, the trained model can generate new mazes that have never appeared in the original game. It can even replace background (static objects) and foreground (dynamic objects) with different images!

As the authors say, applying reinforcement learning algorithms to real world tasks requires accurate simulation of that task. Currently designing such simulations is expensive and time-consuming. Using neural networks instead of hand-written simulations may help to solve these problems.

Paper: https://cdn.arstechnica.net/wp-content/uploads/2020/05/Nvidia_GameGAN_Research.pdf
Blog: https://blogs.nvidia.com/blog/2020/05/22/gamegan-research-pacman-anniversary/
Github Page: https://nv-tlabs.github.io/gameGAN/

#GAN #RL
​​Nvidia announced new card RTX 3090

RTX 3090 is roughly 2 times more powerful than 2080.
There is probably no point in getting 3080 because RAM volume is only 10G.

But what really matters, is how it was presented. Purely technological product for mostly proffesionals, techheads and gamers was presented with absolute brialliancy. That is much more exciting then the release itself.

YouTube: https://www.youtube.com/watch?v=E98hC9e__Xs

#Nvidia #GPU #techstack
​​NVidia released a technology to change face alignment on video

Nvidia has unveiled AI face-alignment that means you're always looking at the camera during video calls. Its new Maxine platform uses GANs to reconstruct the unseen parts of your head β€” just like a deepfake.

Link: https://www.theverge.com/2020/10/5/21502003/nvidia-ai-videoconferencing-maxine-platform-face-gaze-alignment-gans-compression-resolution

#NVidia #deepfake #GAN
Unsupervised 3D Neural Rendering of Minecraft Worlds

Work on unsupervised neural rendering framework for generating photorealistic images of Minecraft (or any large 3D block worlds).

Why this is cool: this is a step towards better graphics for games.

Project Page: https://nvlabs.github.io/GANcraft/
YouTube: https://www.youtube.com/watch?v=1Hky092CGFQ&t=2s

#GAN #Nvidia #Minecraft
​​πŸ”₯Alias-Free Generative Adversarial Networks (StyleGAN3) release

King is dead! Long live the King! #StyleGAN2 was #SOTA and default standard for generating images. #Nvidia released update version, which will lead to more realistic images generated by the community.

Article: https://nvlabs.github.io/stylegan3/
GitHub: https://github.com/NVlabs/stylegan3
Colab: https://colab.research.google.com/drive/1BXNHZBai-pXtP-ncliouXo_kUiG1Pq7M

#GAN #dl