[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)

https://github.com/Garfield-kh/PoseTriplet



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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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Kickstart your developer journey with free courses and cash rewards for you time in one place 📚💰

Use code "aideeplearning" to gain access: https://bit.ly/3KU21bq 👈

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EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks

Official PyTorch implementation of the CVPR 2022 paper.

Project page: https://nvlabs.github.io/eg3d/

Paper: https://arxiv.org/abs/2112.07945

Source code: https://github.com/NVlabs/eg3d


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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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👋 Welcome to
@realgroupforprogrammer 👋

𝗟𝗲𝗮𝗿𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 👨‍💻
𝗟𝗲𝗮𝗿𝗻 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗛𝗮𝗰𝗸𝗶𝗻𝗴 🚀
𝗟𝗲𝗮𝗿𝗻 𝗕𝗹𝗮𝗰𝗸𝗛𝗮𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 💙
𝗔𝗻𝗱 𝗺𝘂𝗰𝗵 𝗺𝗼𝗿𝗲 𝗹𝗮𝘁𝗲𝘀𝘁 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗺𝗲𝘁𝗵𝗼𝗱𝘀, 𝘁𝗶𝗽𝘀 𝗮𝗻𝗱 𝘁𝗿𝗶𝗰𝗸𝘀.

💻 𝗛𝗲𝗿𝗲 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗹𝗲𝗮𝗿𝗻 :- 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴, 𝗛𝗮𝗰𝗸𝗶𝗻𝗴, 𝗖𝗿𝗮𝗰𝗸𝗶𝗻𝗴, 𝗪𝗲𝗯 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, 𝗔𝗽𝗽 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲, 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲, 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴, 𝗚𝗿𝗮𝗽𝗵𝗶𝗰 𝗱𝗲𝘀𝗶𝗴𝗻, 𝗔𝗻𝗶𝗺𝗮𝘁𝗶𝗼𝗻, 𝗩𝗶𝗱𝗲𝗼 𝗲𝗱𝗶𝘁𝗶𝗻𝗴, 𝗣𝗵𝗼𝘁𝗼𝗴𝗿𝗮𝗽𝗵𝘆, 𝗣𝗵𝗼𝘁𝗼𝘀 𝗲𝗱𝗶𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗺𝗮𝗻𝘆 𝗺𝗼𝗿𝗲 𝗹𝗼𝘁𝘀 𝗼𝗳 𝘁𝗵𝗶𝗻𝗴 𝗶𝗻 𝗳𝗿𝗲𝗲 📚🏅🎖

✅ 𝗔 𝗰𝗹𝗲𝗮𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝘆 𝗳𝗼𝗿 𝗴𝗲𝗲𝗸𝘀.

𝗚𝗲𝘁 𝗕𝘂𝗴 𝗕𝗼𝘂𝗻𝘁𝘆, 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴, 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗛𝗮𝗰𝗸𝗶𝗻𝗴, 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 & 𝗹𝗼𝘁 𝗺𝗼𝗿𝗲 𝗹𝗮𝘁𝗲𝘀𝘁 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗯𝗮𝘀𝗲𝗱 𝗲𝗕𝗼𝗼𝗸𝘀.

𝗜𝗻 𝘁𝗵𝗶𝘀 𝗖𝗵𝗮𝗻𝗻𝗲𝗹, 𝗬𝗼𝘂 𝘄𝗶𝗹𝗹 𝗴𝗲𝘁 𝗨𝗱𝗲𝗺𝘆 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀, 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝗿𝗮 𝗖𝗼𝘂𝗿𝘀𝗲𝘀, & 𝗙𝗿𝗲𝗲𝗢𝗻𝗹𝗶𝗻𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀.

𝙁𝙤𝙧 𝙛𝙧𝙚𝙚 𝙘𝙤𝙪𝙧𝙨𝙚𝙨,𝙗𝙤𝙤𝙠𝙨,𝙥𝙧𝙤𝙟𝙚𝙘𝙩𝙨,𝙞𝙣𝙩𝙚𝙧𝙣𝙨𝙝𝙞𝙥𝙨,𝙥𝙡𝙖𝙘𝙚𝙢𝙚𝙣𝙩𝙨 𝙖𝙣𝙙 𝙟𝙤𝙗𝙨 𝙧𝙚𝙡𝙖𝙩𝙚𝙙 𝙢𝙖𝙩𝙚𝙧𝙞𝙖𝙡𝙨 𝙖𝙣𝙙 𝙪𝙥𝙙𝙖𝙩𝙚𝙨 𝙟𝙤𝙞𝙣 𝙤𝙪𝙧 𝙩𝙚𝙡𝙚𝙜𝙧𝙖𝙢 𝙘𝙝𝙖𝙣𝙣𝙚𝙡:

https://t.iss.one/realgroupforprogrammer

𝗦𝗼 𝘄𝗵𝗮𝘁 𝗮𝗿𝗲 𝘆𝗼𝘂 𝘄𝗮𝗶𝘁𝗶𝗻𝗴 𝗳𝗼𝗿?
𝗝𝗼𝗶𝗻 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄👍

https://t.iss.one/realgroupforprogrammer

EasyMocap is an open-source toolbox for markerless human motion capture and novel view synthesis from RGB videos. In this project, we provide a lot of motion capture demos in different settings.

source code: https://github.com/zju3dv/EasyMocap


Paper : https://dl.acm.org/doi/abs/10.1145/3528233.3530704

Colab: https://colab.research.google.com/drive/1Cyvu_lPFUajr2RKt6yJIfS3HQIIYl6QU?usp=sharing


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Free Data Science Courses - Register Now | 365 Data Science

Register for FREE and get access to our online courses by top industry experts. Get a certificate and become a data scientist, data analyst, or business analyst.

https://365datascience.com/free-days-2022/?utm_medium=paid&utm_source=influencer&utm_campaign=2022-nov-free-days-alex-wang-in&utm_content=alex-wang

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Unifying Flow, Stereo and Depth Estimation

Project Page: https://haofeixu.github.io/unimatch/

PAPER: https://arxiv.org/abs/2211.05783

Colab : https://colab.research.google.com/drive/1r5m-xVy3Kw60U-m5VB-aQ98oqqg_6cab?usp=sharing

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GALACTICA is a general-purpose scientific language model. It is trained on a large corpus of scientific text and data. It can perform scientific NLP tasks at a high level, as well as tasks such as citation prediction, mathematical reasoning, molecular property prediction and protein annotation. More information is available at galactica.org.

PAPER: https://arxiv.org/pdf/2211.09085v1.pdf
SOURCE CODE: https://github.com/paperswithcode/galai

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Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild

Paper:
https://arxiv.org/pdf/2207.10660.pdf

Github:
https://github.com/facebookresearch/omni3d

Project page:
https://garrickbrazil.com/omni3d/

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Learning Video Representations from Large Language Models

Paper:
https://arxiv.org/abs/2212.04501

Github:
https://github.com/facebookresearch/lavila

Colab:
https://huggingface.co/spaces/nateraw/lavila

Project page:
https://facebookresearch.github.io/LaViLa/

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🔥 Machine Learning Operations (MLOps) Specialization Course Demo

# FREE CLASS

Learn to Design production-ready ML Pipelines to Build, Train and Deploy your Machine learning models on AWS, Azure, GCP & Open- Source tools

📈 Key Highlights of course
✔️ 40 Hours of Live sessions from Industrial Experts
✔️ 50+ Live Hands-on Labs
✔️ 5+ Real-time industrial projects
✔️ One-on-One with Industry Mentors

👉🏻 Registration Link
https://bit.ly/mlops-demo-course

🧑🏻‍🎓 What You Will Learn?
▪️Introduction to ML and MLOps stages
▪️Introduction to Git & CI/CD
▪️Docker & Kubernetes Overview
▪️Kubernetes Deployment Strategy
▪️Introduction to Model Management
▪️Feature Store
▪️Cloud ML Services 101
▪️Kubeflow Intro
▪️Introduction to Model Monitoring
▪️Introduction to Automl tools
▪️Post-Deployment Challenges

☎️ Contact:
Sarath Kumar
+918940876397 / +918778033930

MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications.

2023 lectures are starting in just one day, Jan 9th!

Link to register:
https://introtodeeplearning.com

MIT Introduction to Deep Learning The 2022 lectures can be found here:

https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

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Welcome to the Ultralytics YOLOv8 🚀 notebook! YOLOv8 is the latest version of the YOLO object detection and image segmentation model developed by Ultralytics.
The YOLOv8 models are designed to be fast, accurate, and easy to use, making them an excellent choice for a wide range of object detection and image segmentation tasks.

source code: https://github.com/ultralytics/ultralytics

colab : https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb#scrollTo=t6MPjfT5NrKQ

MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications.

Link to register:
https://introtodeeplearning.com

MIT Introduction to Deep Learning The 2022 lectures can be found here:

https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

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