Papers with Code 2021 : A Year in Review.
Papers with Code indexes various machine learning artifacts β papers, code, results β to facilitate discovery and comparison. Using this data we can get a sense of what the ML community found useful and interesting this year. Below we summarize the top trending papers, libraries and datasets for 2021 on Papers with Code.
https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b
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Papers with Code indexes various machine learning artifacts β papers, code, results β to facilitate discovery and comparison. Using this data we can get a sense of what the ML community found useful and interesting this year. Below we summarize the top trending papers, libraries and datasets for 2021 on Papers with Code.
https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b
ππ@deeplearning_ai
Medium
Papers with Code 2021 : A Year in Review
Papers with Code indexes various machine learning artifactsβββpapers, code, resultsβββto facilitate discovery and comparison. Using thisβ¦
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ββββββ ConvNeXt ββββββ--
Facebook propose ConvNeXt, a pure ConvNet model constructed entirely from standard ConvNet modules. ConvNeXt is accurate, efficient, scalable and very simple in design.
Github: https://github.com/facebookresearch/ConvNeXt
Paper: https://arxiv.org/abs/2201.03545
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Facebook propose ConvNeXt, a pure ConvNet model constructed entirely from standard ConvNet modules. ConvNeXt is accurate, efficient, scalable and very simple in design.
Github: https://github.com/facebookresearch/ConvNeXt
Paper: https://arxiv.org/abs/2201.03545
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#βββββCVPR_2021βββββ
RefineMask: Towards High-Quality Instance Segmentation
with Fine-Grained Features (CVPR 2021)
[paper] : download paper and enjoy
source: use source code and get awesome result
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RefineMask: Towards High-Quality Instance Segmentation
with Fine-Grained Features (CVPR 2021)
[paper] : download paper and enjoy
source: use source code and get awesome result
invite your friends and get latest news and sources on AI
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5TH UG2+ PRIZE CHALLENGE CVPR 2022
$10K PRIZES
http://cvpr2022.ug2challenge.org/
https://docs.google.com/forms/d/e/1FAIpQLSeK0j4cPRNFQbm27qMfaTr27wRQ6tXMV2gmohjaJlbn2fAX0A/viewform
https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FUG2CHALLENGE2022
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$10K PRIZES
http://cvpr2022.ug2challenge.org/
https://docs.google.com/forms/d/e/1FAIpQLSeK0j4cPRNFQbm27qMfaTr27wRQ6tXMV2gmohjaJlbn2fAX0A/viewform
https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FUG2CHALLENGE2022
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The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
https://www.ritchieng.com/the-incredible-pytorch/
https://github.com/ritchieng/the-incredible-pytorch
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https://www.ritchieng.com/the-incredible-pytorch/
https://github.com/ritchieng/the-incredible-pytorch
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GitHub
GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list of tutorials, papers, projects, communities andβ¦
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. - GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list...
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321 Open Source Pytorch Implementation Software Projects
Free and open source pytorch implementation code projects including engines, APIs, generators, and tools.
https://opensourcelibs.com/libs/pytorch-implementation
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t.me/MachineLearning_Programming
.
Free and open source pytorch implementation code projects including engines, APIs, generators, and tools.
https://opensourcelibs.com/libs/pytorch-implementation
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t.me/MachineLearning_Programming
.
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Want to jump ahead in artificial intelligence and/or digital pathology? Excited to share that after 2+ years of development PathML 2.0 is out! An open source #computational #pathology software library created by Dana-Farber Cancer Institute/Harvard Medical School and Weill Cornell Medicine led by Massimo Loda to lower the barrier to entry to #digitalpathology and #artificialintelligence , and streamline all #imageanalysis or #deeplearning workflows.
β Code: https://github.com/Dana-Farber-AIOS/pathml
β Code: https://github.com/Dana-Farber-AIOS/pathml
GitHub
GitHub - Dana-Farber-AIOS/pathml: Tools for computational pathology
Tools for computational pathology. Contribute to Dana-Farber-AIOS/pathml development by creating an account on GitHub.
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Image Super Resolution - PyImageSearch
https://pyimagesearch.com/2022/02/14/image-super-resolution/
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.
https://pyimagesearch.com/2022/02/14/image-super-resolution/
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.
PyImageSearch
Image Super Resolution - PyImageSearch
Understand and apply image super resolution in your work today. Free tutorial and complete code included.
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Multi Task Learning for 3D segmentation
Perception stack of an Autonomous Driving system often contains multiple neural networks working together to predict bounding boxes, segmentation maps, depth maps, lane lines etc. Having a separate neural network for each task creates an heavy impact on system's processing speed.
https://github.com/adithyagaurav/Multi_Task_Learning
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Perception stack of an Autonomous Driving system often contains multiple neural networks working together to predict bounding boxes, segmentation maps, depth maps, lane lines etc. Having a separate neural network for each task creates an heavy impact on system's processing speed.
https://github.com/adithyagaurav/Multi_Task_Learning
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Realtime Object-aware Monocular Depth Estimation in Onboard Systems
Video Paper Bibtex
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Video Paper Bibtex
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FLAG: Flow-based 3D Avatar Generation
from Sparse Observations.
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β FLow-based Avatar Generative
β Conditional distro of body pose
β Exact pose likelihood process
β Invertibility -> oracle latent code
[PAPER] [Project Page]
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from Sparse Observations.
ππ’π π‘π₯π’π π‘ππ¬:
β FLow-based Avatar Generative
β Conditional distro of body pose
β Exact pose likelihood process
β Invertibility -> oracle latent code
[PAPER] [Project Page]
invite your friends πΉπΉ
@Deeplearning_ai
π44π₯13π1
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
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
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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 (TΓΌbingen)
https://github.com/dair-ai/ML-YouTube-Courses
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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 (TΓΌbingen)
https://github.com/dair-ai/ML-YouTube-Courses
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[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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https://github.com/Garfield-kh/PoseTriplet
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GitHub
GitHub - Garfield-kh/PoseTriplet: [CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination underβ¦
[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral) - 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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https://github.com/nebuly-ai/nebulgym
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GitHub
GitHub - nebuly-ai/nos: Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through realβ¦
Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas - Effortless optimization at its finest! - nebuly...
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Kickstart your developer journey with free courses and cash rewards for you time in one place ππ°
Use code "aideeplearning" to gain access: https://bit.ly/3KU21bq π
StackUp is a platform for devs where you can learn programming & Web3.0 technologies, all while earning. Get rewarded for completing a variety of learning quests.
With new campaigns each week, you can earn from a pool of over 10 000USD in cash rewards each month. This month's campaign has a total pool of 30 000USD worth of rewards! π
Use code "aideeplearning" to gain access: https://bit.ly/3KU21bq π
StackUp is a platform for devs where you can learn programming & Web3.0 technologies, all while earning. Get rewarded for completing a variety of learning quests.
With new campaigns each week, you can earn from a pool of over 10 000USD in cash rewards each month. This month's campaign has a total pool of 30 000USD worth of rewards! π
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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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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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