Generative Occupancy Fields for 3D Surface-Aware Image Synthesis (NeurIPS 2021)

Project Page Paper Github


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EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks

https://youtu.be/cXxEwI7QbKg


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@Deeplearning_ai

🛸UFO: segmentation @140+ FPS🛸

👉Unified Transformer Framework for Co-Segmentation, Co-Saliency & Salient Object Detection. All in one!


𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Unified framework for co-segmentation
✅Co-segmentation, co-saliency, saliency
✅Block for long-range dependencies
✅Able to reach for 140 FPS in inference
✅The new SOTA on multiple datasets
✅Source code under MIT License


[PAPER] [Source Code]

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If you are learning Machine Learning and wants to make end-to-end Machine Learning real-world projects, then this website can be a great resource for you.

It has project bundle(Dragon bundle) comprising more than 550+ real-world projects in ML, DL, DS, CV and NLP and PYTHON3.

More details are showned in the image above.

- Each project comes with required Dataset, complete source code(Python3) and documentation along with explanatory comments so that even beginner can understand.

- Life time access and projects are getting updates each month.

You can download the list of complete 550+ projects from our website.

Visit our website for more information.
Website Link:
https://tensorprojects.com/dragonbundle

At DAIR.AI we heart open education. We are excited to share some of the best and most recent machine learning courses available on YouTube.

Hot topics:
1. Stanford CS229: Machine Learning
2. Practical Deep Learning for Coders (2020)
3. Deep Unsupervised Learning
4. Advanced NLP
5. Deep Learning for Computer Vision
6. Deep Reinforcement Learning
7. Full Stack Deep Learning
8. Self-Driving Cars (Tübingen)

https://github.com/dair-ai/ML-YouTube-Courses

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Free programming courses & quests with cash rewards for your time in one place 📚💰

StackUp [app.stackup.dev] is a platform made for devs where you can learn about programming languages like Rust, Python, Go, Solidity, and other technologies, and earn while learning. Rewards are given after successful completion of quests.

With new campaigns every week, you can earn from a pool of over 10,000USD in cash rewards each month!

To sign up use code "machinelearning0" and gain early access: https://bit.ly/3FpfqHr

Hope it helps you to level up in the community and master different tools essential to your career as a developer! 🚀

@deeplearning_ai

Lightweight Python library for adding real-time object tracking to any detector.

https://github.com/tryolabs/norfair


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Accelerate AI training in a few lines of code without changing the training setup.


https://github.com/nebuly-ai/nebulgym



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Free courses and quests in Coding & Web3.0 with cash rewards worth of 30 000USD 👇
https://bit.ly/3FpfqHr

Use code: "machinelearning0" when signing up to get access and start learning 🙌

PaMIR: Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstruction.

Paper: https://arxiv.org/abs/2007.03858

Project Page: http://www.liuyebin.com/pamir/pamir.html

Source code: https://github.com/ZhengZerong/PaMIR


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@MachineLearning_Programming

CVPR 2022 Open Access...


Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.

https://openaccess.thecvf.com/CVPR2022?day=2022-06-21



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Harvard CS109A #DataScience course materials — huge collection free & open!

1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...

https://harvard-iacs.github.io/2019-CS109A/pages/materials.html


It will be really useful for you


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Pycharm keyboard shortcuts


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You don't need to spend several $𝟭𝟬𝟬𝟬𝘀 to learn Data Science.❌

Stanford University, Harvard University & Massachusetts Institute of Technology is providing free courses.💥

Here's 8 free Courses that'll teach you better than the paid ones:


1. CS50’s Introduction to Artificial Intelligence with Python (Harvard)

https://lnkd.in/d9CkkfGK

2. Data Science: Machine Learning (Harvard)

https://lnkd.in/dQ7zkCv9

3. Artificial Intelligence (MIT)

https://lnkd.in/dG5BCPen

4. Introduction to Computational Thinking and Data Science (MIT)

https://lnkd.in/ddm5Ckk9

5. Machine Learning (MIT)

https://lnkd.in/dJEjStCw

6. Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (MIT)

https://lnkd.in/dkpyt6qr

7. Statistical Learning (Stanford)

https://lnkd.in/dymn4hbD

8. Mining Massive Data Sets (Stanford)

📍https://lnkd.in/d2uf-FkB



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@MachineLearning_Programming

Deep Face Restoartion: Denoise, Super-Resolution, Deblur and Artifact Removal


Table of Contents
* Surveys
* Deep Blind Face Restoration
* Deep Face Super-Resolution
* Deep Face Deblurring
* Deep Face Denoising
* Deep Face Artifact Removal
* Other Related Works
* Image Quality Assessment
* Benchmark Datasets
* Recommended Datasets
* All Datasets

Paper: https://arxiv.org/pdf/2211.02831v1.pdf

source code: https://github.com/taowangzj/awesome-face-restoration

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@MachineLearning_Programming