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๐ท๏ธ๐ท๏ธ GenN2N: Generative NeRF2NeRF Translation.๐ท๏ธ๐ท๏ธ
Key Features:
* Collaborative Excellence.
* Advanced 3D VAE-GAN Architecture
* Universal NeRF Editing
* Contrastive Learning
* Optimized Performance
[Paper]
[Source Code]
[Project Page]
Join our community: @deeplearning_ai
Key Features:
* Collaborative Excellence.
* Advanced 3D VAE-GAN Architecture
* Universal NeRF Editing
* Contrastive Learning
* Optimized Performance
[Paper]
[Source Code]
[Project Page]
Join our community: @deeplearning_ai
๐25โค2๐ฅ1
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Neural Bodies with Clothes: Overview
Introduction: Neural-ABC, a cutting-edge parametric model developed by the University of Science & Technology of China, innovatively represents clothed human bodies.
Key Features:
โ Novel approach for modeling clothed human figures.
โ Unified framework accommodating various clothing types.
โ Consistent representation of both body and clothing.
โ Enables seamless modification of identity, shape, clothing, and pose.
โ Extensive dataset with detailed clothing information.
Explore More:
๐ปProject Details: Discover More
๐Read the Paper: Access Here
๐ปSource Code: Explore on GitHub
Relevance: #artificialintelligence #machinelearning #AI #deeplearning #computervision
join our community:
๐ @deeplearning_ai
Introduction: Neural-ABC, a cutting-edge parametric model developed by the University of Science & Technology of China, innovatively represents clothed human bodies.
Key Features:
โ Novel approach for modeling clothed human figures.
โ Unified framework accommodating various clothing types.
โ Consistent representation of both body and clothing.
โ Enables seamless modification of identity, shape, clothing, and pose.
โ Extensive dataset with detailed clothing information.
Explore More:
๐ปProject Details: Discover More
๐Read the Paper: Access Here
๐ปSource Code: Explore on GitHub
Relevance: #artificialintelligence #machinelearning #AI #deeplearning #computervision
join our community:
๐ @deeplearning_ai
๐12๐ฅ7โค6
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๐ 6Img-to-3D driving scenarios ๐
๐ฎโโ๏ธ EPFL (+ Continental) unveils 6Img-to-3D, novel transformer-based encoder-renderer method to create 3D onbounded outdoor driving scenarios with only six pics
๐ฅบ Review: https://shorturl.at/dZ018
๐คจ Paper: arxiv.org/pdf/2404.12378.pdf
๐ Project: 6img-to-3d.github.io/
๐ Code: github.com/continental/6Img-to-3D
โ https://t.me/deeplearning_ai
๐ฎโโ๏ธ EPFL (+ Continental) unveils 6Img-to-3D, novel transformer-based encoder-renderer method to create 3D onbounded outdoor driving scenarios with only six pics
๐ฅบ Review: https://shorturl.at/dZ018
๐คจ Paper: arxiv.org/pdf/2404.12378.pdf
๐ Project: 6img-to-3d.github.io/
๐ Code: github.com/continental/6Img-to-3D
โ https://t.me/deeplearning_ai
๐19โค1
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๐ Introducing UniRef++: Advanced Object Segmentation in Spatial and Temporal Domains
๐ Key Features:
Unified Model: UniRef++ seamlessly handles segmentation tasks:
โ Referring Image Segmentation (RIS)
โ Few-Shot Segmentation (FSS)
โ Referring Video Object Segmentation (RVOS)
โ Video Object Segmentation (VOS)
Core Component: UniFusion module
โ Integrates reference information efficiently
โ Utilizes flash attention for high efficiency
Compatibility: Acts as a plug-in for foundational models like SAM
๐ UniRef++ is the official extended implementation from ICCV 2023's UniRef.
Stay tuned for more updates!
๐ Code: https://github.com/FoundationVision/UniRef
๐คจ Paper: [Paper link]
โ https://t.me/deeplearning_ai
๐ Key Features:
Unified Model: UniRef++ seamlessly handles segmentation tasks:
โ Referring Image Segmentation (RIS)
โ Few-Shot Segmentation (FSS)
โ Referring Video Object Segmentation (RVOS)
โ Video Object Segmentation (VOS)
Core Component: UniFusion module
โ Integrates reference information efficiently
โ Utilizes flash attention for high efficiency
Compatibility: Acts as a plug-in for foundational models like SAM
๐ UniRef++ is the official extended implementation from ICCV 2023's UniRef.
Stay tuned for more updates!
๐ Code: https://github.com/FoundationVision/UniRef
๐คจ Paper: [Paper link]
โ https://t.me/deeplearning_ai
๐18โค8๐ข2
India's Largest Free Webinar on LLMs especially focused on the recently released LLAMA-3 by Meta.
How do you use these models?
How can you create apps with them?
Join our free workshop on to learn how to use Llama 3 and create apps with it.
Register here: https://www.buildfastwithai.com/events/llama-3-deep-dive
You can connect with Founder;
https://www.linkedin.com/in/satvik-paramkusham/
This Event is especially designed for people interested in the field of AI, ML, GenAI & LLMs.
How do you use these models?
How can you create apps with them?
Join our free workshop on to learn how to use Llama 3 and create apps with it.
Register here: https://www.buildfastwithai.com/events/llama-3-deep-dive
You can connect with Founder;
https://www.linkedin.com/in/satvik-paramkusham/
This Event is especially designed for people interested in the field of AI, ML, GenAI & LLMs.
๐14โค3
Learn to deploy Gen Ai Models to production ๐
MLOps Masterclass
Productionizing Generative AI models, Navigating the Landscape of MLOps & LLMOps - Understanding the Synergy
Schedule:
May 25th (Sat) & 26th (Sun), 10AM to 3:30 PM
Register Now๐
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๐ฅ Limited Seats Available!
โ๏ธ Contact:
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+918940876397 / +918778033930
MLOps Masterclass
Productionizing Generative AI models, Navigating the Landscape of MLOps & LLMOps - Understanding the Synergy
Schedule:
May 25th (Sat) & 26th (Sun), 10AM to 3:30 PM
Register Now๐
https://bit.ly/mlops-masterclass
๐ฅ Limited Seats Available!
โ๏ธ Contact:
Sarath Kumar
+918940876397 / +918778033930
๐15โค2
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๐ Explore SCRFD: High-Efficiency, High-Accuracy Face Detection ๐
Unlock next-level face detection capabilities with SCRFD โ efficiency and accuracy in one solution!
๐ Performance at a Glance:
โ Model range: SCRFD_500M to SCRFD_34G
โ Accuracy up to 96.06%
โ Inference as fast as 3.6 ms
๐ Explore more and consider starring our repo for updates:
--- GitHub Repository.
--- Paper
#AI #MachineLearning #FaceDetection #TechInnovation #DeepLearning
โ https://t.me/deeplearning_ai
Unlock next-level face detection capabilities with SCRFD โ efficiency and accuracy in one solution!
๐ Performance at a Glance:
โ Model range: SCRFD_500M to SCRFD_34G
โ Accuracy up to 96.06%
โ Inference as fast as 3.6 ms
๐ Explore more and consider starring our repo for updates:
--- GitHub Repository.
--- Paper
#AI #MachineLearning #FaceDetection #TechInnovation #DeepLearning
โ https://t.me/deeplearning_ai
๐16โค5๐ฅ1
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๐ Discover the Power of Fine-Grained Gaze Estimation with L2CS-Net! ๐
๐ Key Features:
โ Advanced Architecture: Built using state-of-the-art neural network structures.
โ Versatile Utilities: Packed with utility functions and classes for seamless integration.
โ Robust Data Handling: Efficient data loading, preprocessing, and augmentation.
โ Comprehensive Training & Testing: Easy-to-follow scripts for training and testing your models.
๐ Live Demo:
Visualize the power of L2CS-Net with your own video:
๐ Join Us:
Star our repo on GitHub and be part of the innovative community pushing the boundaries of gaze estimation. Your support drives us forward!
๐ GitHub Repository
Let's advance gaze estimation together! ๐๐ #GazeEstimation #DeepLearning #AI #MachineLearning #ComputerVision
๐ Key Features:
โ Advanced Architecture: Built using state-of-the-art neural network structures.
โ Versatile Utilities: Packed with utility functions and classes for seamless integration.
โ Robust Data Handling: Efficient data loading, preprocessing, and augmentation.
โ Comprehensive Training & Testing: Easy-to-follow scripts for training and testing your models.
๐ Live Demo:
Visualize the power of L2CS-Net with your own video:
๐ Join Us:
Star our repo on GitHub and be part of the innovative community pushing the boundaries of gaze estimation. Your support drives us forward!
๐ GitHub Repository
Let's advance gaze estimation together! ๐๐ #GazeEstimation #DeepLearning #AI #MachineLearning #ComputerVision
๐14โค5๐คฉ1
FREE Machine Learning & Artificial Intelligence Certified Courses
๐๐
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Amazing premium resources only for my subscribers
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Amazing premium resources only for my subscribers
๐ Free Data Science Books
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๐ Learn Generative AI
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Free Access to our paid data science community today:
๐๐
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Hope you like it ๐
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๐ฐ Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data
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๐ Introducing Emotion Recognition with ONNX Runtime!
Transform your projects with real-time face detection and emotion recognition. Dive into our latest repo and see the magic unfold!
๐ Key Features:
* Real-time face detection with ONNX models.
* Accurate emotion recognition from detected faces.
* Live visualization of emotion scores.
โญ๏ธ Star our repo and elevate your AI projects: Emotion Recognition on GitHub
Join us on this exciting journey and letโs push the boundaries of AI together! ๐๐ฉโ๐ป๐จโ๐ป
โ https://github.com/Shohruh72
โ https://t.me/deeplearning_ai
Transform your projects with real-time face detection and emotion recognition. Dive into our latest repo and see the magic unfold!
๐ Key Features:
* Real-time face detection with ONNX models.
* Accurate emotion recognition from detected faces.
* Live visualization of emotion scores.
โญ๏ธ Star our repo and elevate your AI projects: Emotion Recognition on GitHub
Join us on this exciting journey and letโs push the boundaries of AI together! ๐๐ฉโ๐ป๐จโ๐ป
โ https://github.com/Shohruh72
โ https://t.me/deeplearning_ai
๐25โค2๐ฅ2๐2
๐ Join Our Team as a Senior Data Researcher at Wunder Fund! ๐
๐ Location: Remote/Relocation to various countries
๐ธ Salary: $5k-$7k+ per month (USD or Crypto)
At wunderfund.io we've been in the HFT trading game since 2014 and our daily trading volume is around $8B. We're looking for a Senior Data Researcher to lead our neural networks direction.
๐พWhat Youโll Do:
- Train models, test hypotheses, and achieve maximum model accuracy
- Work with top-tier programmers, mathematicians, and physicists
๐คWhat You Will Need:
- Proficiency in Python and Mathematics
- Experience with Kaggle (Master/Grandmaster)
- Success in training transformers and LSTM
๐ Learn More & Apply
๐ Location: Remote/Relocation to various countries
๐ธ Salary: $5k-$7k+ per month (USD or Crypto)
At wunderfund.io we've been in the HFT trading game since 2014 and our daily trading volume is around $8B. We're looking for a Senior Data Researcher to lead our neural networks direction.
๐พWhat Youโll Do:
- Train models, test hypotheses, and achieve maximum model accuracy
- Work with top-tier programmers, mathematicians, and physicists
๐คWhat You Will Need:
- Proficiency in Python and Mathematics
- Experience with Kaggle (Master/Grandmaster)
- Success in training transformers and LSTM
๐ Learn More & Apply
๐19โค3
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3D StreetUnveiler with Semantic-Aware 2DGS
โ https://github.com/DavidXu-JJ/StreetUnveiler
โ https://t.me/deeplearning_ai
โ https://github.com/DavidXu-JJ/StreetUnveiler
โ https://t.me/deeplearning_ai
๐12๐ฅ4
Are you struggling with invoking functions, passing arguments, or handling return values in Large Language Models (LLMs)?
Whether youโre a seasoned developer or just starting your journey in Gen AI.
In this session, weโll explore the fascinating world of invoking functions using LLMs.
1. Introduction to LLMs.
2. Function Calls: Basics and Syntax.
3. Live Coding Examples.
4. Q&A Session.
Register For Free:
๐ Date: 14th June, Friday
โฐ Time: 9 PM, IST
๐ Link : https://www.buildfastwithai.com/events/function-calling-with-llms
Whether youโre a seasoned developer or just starting your journey in Gen AI.
In this session, weโll explore the fascinating world of invoking functions using LLMs.
1. Introduction to LLMs.
2. Function Calls: Basics and Syntax.
3. Live Coding Examples.
4. Q&A Session.
Register For Free:
๐ Date: 14th June, Friday
โฐ Time: 9 PM, IST
๐ Link : https://www.buildfastwithai.com/events/function-calling-with-llms
๐12โค1
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Depth Anything2: Unleashing the Power of Large-Scale Unlabeled Data
This work presents Depth Anything, a highly practical solution for robust monocular depth estimation by training on a combination of 1.5M labeled images and 62M+ unlabeled images.
Explore More:
๐ปSource Code: Explore on GitHub
๐ปProject Details: Discover More
๐Read the Paper: Access Here
โ https://t.me/deeplearning_ai
This work presents Depth Anything, a highly practical solution for robust monocular depth estimation by training on a combination of 1.5M labeled images and 62M+ unlabeled images.
Explore More:
๐ปSource Code: Explore on GitHub
๐ปProject Details: Discover More
๐Read the Paper: Access Here
โ https://t.me/deeplearning_ai
๐ฅ9๐7โค5
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Grounding DINO 1.5
IDEA Research's Most Capable Open-World Object Detection Model Series.
Explore More:
๐ปSource Code: Explore on GitHub
๐ปTry DEMO: Discover More
๐Read the Paper: Access Here
โ https://t.me/deeplearning_ai
IDEA Research's Most Capable Open-World Object Detection Model Series.
Explore More:
๐ปSource Code: Explore on GitHub
๐ปTry DEMO: Discover More
๐Read the Paper: Access Here
โ https://t.me/deeplearning_ai
๐12๐ฅ3๐2โค1
๐ MLOps Market to reach US$4 Billion in 2025
Unleash MLOps Mastery - FREE Training on AWS, Azure, GCP & Open-source!
Navigating the Landscape of MLOps & LLMOps
๐ Unlock ML deployment secrets on top clouds & open source.
๐ก Dive into data management insights.
๐ ๏ธ Harness the latest MLOps tools.
๐ฅ Real-time expert interaction.
๐ฅ Limited spots! Enroll now:
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๐ Share with ML enthusiasts! #MLOps #AI #TechTraining
Unleash MLOps Mastery - FREE Training on AWS, Azure, GCP & Open-source!
Navigating the Landscape of MLOps & LLMOps
๐ Unlock ML deployment secrets on top clouds & open source.
๐ก Dive into data management insights.
๐ ๏ธ Harness the latest MLOps tools.
๐ฅ Real-time expert interaction.
๐ฅ Limited spots! Enroll now:
https://bit.ly/mlops-free-class
๐ Share with ML enthusiasts! #MLOps #AI #TechTraining
๐15โค6๐ฅ1
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โ๏ธ IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination.
https://github.com/zju3dv/IntrinsicAnything
โ https://t.me/deeplearning_ai
https://github.com/zju3dv/IntrinsicAnything
โ https://t.me/deeplearning_ai
๐11๐ฅ1
1๏ธโฃ Basics of Data Science
๐ท Statistics and Probability
โพ๏ธ Statistics & Probability
๐ท Linear Algebra
โฝ๏ธ Essence of Linear Algebra
2๏ธโฃ Programming Language\
๐ท Python
โพ๏ธ Learn Python 3
3๏ธโฃ Data Analysis and Manipulation
๐ท Pandas Library
โพ๏ธ Pandas Documentation
๐ท Data Preparation with Pandas
โพ๏ธ Data Wrangling with Pandas
๐ท NumPy Library
โพ๏ธ NumPy Documentation
4๏ธโฃ Data Visualization
๐ท Matplotlib and Seaborn Library
โพ๏ธ Matplotlib / Seaborn
๐ทTableau Public Platform
โพ๏ธ Tableau Public
5๏ธโฃ Principles of Machine Learning
๐ท scikit-learn Library
โพ๏ธ scikit-learn
6๏ธโฃ Learning Algorithms
๐ท Hands-On Machine Learning Book
โพ๏ธ Hands-On ML
7๏ธโฃ Deep Learning
๐ท TensorFlow Library
โพ๏ธ TensorFlow Tutorial
๐ท PyTorch Library
โพ๏ธ PyTorch Documentation
8๏ธโฃ Big Data Technologies
๐ท Spark Framework Course
โพ๏ธ Spark Course
9๏ธโฃ Advanced Topics
๐ท Natural Language Processing Course in Python
โพ๏ธ NLP in Python
1๏ธโฃ Share Your Projects on Kaggle and GitHub
๐ท Kaggle Platform
โพ๏ธ Kaggle
๐ท GitHub Platform
โพ๏ธ GitHub
Happy Learning! ๐
๐ท Statistics and Probability
โพ๏ธ Statistics & Probability
๐ท Linear Algebra
โฝ๏ธ Essence of Linear Algebra
2๏ธโฃ Programming Language\
๐ท Python
โพ๏ธ Learn Python 3
3๏ธโฃ Data Analysis and Manipulation
๐ท Pandas Library
โพ๏ธ Pandas Documentation
๐ท Data Preparation with Pandas
โพ๏ธ Data Wrangling with Pandas
๐ท NumPy Library
โพ๏ธ NumPy Documentation
4๏ธโฃ Data Visualization
๐ท Matplotlib and Seaborn Library
โพ๏ธ Matplotlib / Seaborn
๐ทTableau Public Platform
โพ๏ธ Tableau Public
5๏ธโฃ Principles of Machine Learning
๐ท scikit-learn Library
โพ๏ธ scikit-learn
6๏ธโฃ Learning Algorithms
๐ท Hands-On Machine Learning Book
โพ๏ธ Hands-On ML
7๏ธโฃ Deep Learning
๐ท TensorFlow Library
โพ๏ธ TensorFlow Tutorial
๐ท PyTorch Library
โพ๏ธ PyTorch Documentation
8๏ธโฃ Big Data Technologies
๐ท Spark Framework Course
โพ๏ธ Spark Course
9๏ธโฃ Advanced Topics
๐ท Natural Language Processing Course in Python
โพ๏ธ NLP in Python
1๏ธโฃ Share Your Projects on Kaggle and GitHub
๐ท Kaggle Platform
โพ๏ธ Kaggle
๐ท GitHub Platform
โพ๏ธ GitHub
Happy Learning! ๐
โค21๐16๐ฑ3๐1
output_demo.gif
21.2 MB
๐FACE ID: Face Identification ๐
Hello tech enthusiasts! ๐
Our project leverages the power of ONNX Runtime to deliver high-accuracy face identification.
๐ Check out our project and see it in action!
๐ Visit our GitHub Repository: FACE ID
We need your support to make this project even better! Hereโs how you can help:
โญ๏ธ Star our repository to show your appreciation and help us gain more visibility.
๐ Share with your network to spread the word about AdaFace.
๐ Give us feedback by reviewing the code and suggesting improvements.
Thank you for being part of our journey. Let's create something amazing! ๐
#FaceRecognition #ONNX #AdaFace #GitHub #OpenSource #TechInnovation
Happy Learning! ๐
Hello tech enthusiasts! ๐
Our project leverages the power of ONNX Runtime to deliver high-accuracy face identification.
๐ Check out our project and see it in action!
๐ Visit our GitHub Repository: FACE ID
We need your support to make this project even better! Hereโs how you can help:
โญ๏ธ Star our repository to show your appreciation and help us gain more visibility.
๐ Share with your network to spread the word about AdaFace.
๐ Give us feedback by reviewing the code and suggesting improvements.
Thank you for being part of our journey. Let's create something amazing! ๐
#FaceRecognition #ONNX #AdaFace #GitHub #OpenSource #TechInnovation
Happy Learning! ๐
๐ฅ9๐6โค5๐1