Open-Vocabulary SAM
[Paper] [Project Page] [Hugging Face Demo]
Source Code: https://github.com/harboryuan/ovsam?tab=readme-ov-file
join our community:
๐ @deeplearning_ai
[Paper] [Project Page] [Hugging Face Demo]
Source Code: https://github.com/harboryuan/ovsam?tab=readme-ov-file
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๐ @deeplearning_ai
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PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
[Paper] [Project Page] [Model Card]
[๐ค Demo (Realistic)] [๐ค Demo (Stylization)]
๐ Key Features:
1. Rapid customization within seconds, with no additional LoRA training.
2. Ensures impressive ID fidelity, offering diversity, promising text controllability, and high-quality generation.
3. Can serve as an Adapter to collaborate with other Base Models alongside LoRA modules in community.
[Paper] [Project Page] [Model Card]
[๐ค Demo (Realistic)] [๐ค Demo (Stylization)]
๐ Key Features:
1. Rapid customization within seconds, with no additional LoRA training.
2. Ensures impressive ID fidelity, offering diversity, promising text controllability, and high-quality generation.
3. Can serve as an Adapter to collaborate with other Base Models alongside LoRA modules in community.
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Depth Anything
Unleashing the Power of Large-Scale Unlabeled Data
[Paper] [Code] [Demo]
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๐ @deeplearning_ai
Unleashing the Power of Large-Scale Unlabeled Data
[Paper] [Code] [Demo]
join our community:
๐ @deeplearning_ai
MLOps Masterclass
๐ฅClosing registration soon!
Navigating the Landscape of MLOps & LLMOps - Understanding the Synergy
Register Now๐
https://bit.ly/mlops-masterclass
Schedule:
February 24th (Sat) & 25th (Sun), 10AM to 2:30 PM
Highlights of this Masterclass:
โช๏ธMLOps Introduction
โช๏ธMLOps for LLM's (LLMOps)
โช๏ธMLOps and Stages
โช๏ธAWS SageMaker
โช๏ธCI/CD for MLOps
โช๏ธAWS MLOps - Build, Train & deploy ML Model
๐ฅ Limited Seats Available!
Register Now๐
https://bit.ly/mlops-masterclass
โ๏ธ Contact:
Sarath Kumar
+918940876397 / +918778033930
๐ฅClosing registration soon!
Navigating the Landscape of MLOps & LLMOps - Understanding the Synergy
Register Now๐
https://bit.ly/mlops-masterclass
Schedule:
February 24th (Sat) & 25th (Sun), 10AM to 2:30 PM
Highlights of this Masterclass:
โช๏ธMLOps Introduction
โช๏ธMLOps for LLM's (LLMOps)
โช๏ธMLOps and Stages
โช๏ธAWS SageMaker
โช๏ธCI/CD for MLOps
โช๏ธAWS MLOps - Build, Train & deploy ML Model
๐ฅ Limited Seats Available!
Register Now๐
https://bit.ly/mlops-masterclass
โ๏ธ Contact:
Sarath Kumar
+918940876397 / +918778033930
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Awesome-AIGC-3D
A curated list of awesome AIGC 3D papers, inspired by awesome-NeRF.
Source code: https://github.com/hitcslj/awesome-aigc-3d?tab=readme-ov-file
join our community:
๐ @deeplearning_ai
A curated list of awesome AIGC 3D papers, inspired by awesome-NeRF.
Source code: https://github.com/hitcslj/awesome-aigc-3d?tab=readme-ov-file
join our community:
๐ @deeplearning_ai
This channels is for Programmers, Coders, Software Engineers.
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EfficientViT - SAM:69x Faster SAM: Multi-Scale Linear Attention for High-Resolution Dense Prediction
1. Channel: @deeplearning_ai
2.Source Code: https://github.com/mit-han-lab/efficientvit
3. Paper: https://arxiv.org/abs/2402.05008
1. Channel: @deeplearning_ai
2.Source Code: https://github.com/mit-han-lab/efficientvit
3. Paper: https://arxiv.org/abs/2402.05008
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๐๐ Magic-Me: Identity-Specific Video ๐๐
๐hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel Video Custom Diffusion (VCD) framework
โ High-Quality ID-specific videos generation
โ Improvement in aligning IDs-images and text
โ Robust 3D Gaussian Noise Prior for denoising
โ Better Inter-frame correlation / video consistency
โ New modules F-VCD/T-VCD for videos upscale
โ New train with masked loss by prompt-to-segmentation
hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
๐Channel: @deeplearning_ai
๐Paper https://arxiv.org/pdf/2402.09368.pdf
๐Project https://magic-me-webpage.github.io/
๐Code https://github.com/Zhen-Dong/Magic-Me
๐hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel Video Custom Diffusion (VCD) framework
โ High-Quality ID-specific videos generation
โ Improvement in aligning IDs-images and text
โ Robust 3D Gaussian Noise Prior for denoising
โ Better Inter-frame correlation / video consistency
โ New modules F-VCD/T-VCD for videos upscale
โ New train with masked loss by prompt-to-segmentation
hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
๐Channel: @deeplearning_ai
๐Paper https://arxiv.org/pdf/2402.09368.pdf
๐Project https://magic-me-webpage.github.io/
๐Code https://github.com/Zhen-Dong/Magic-Me
Result.gif
23.1 MB
๐ Discover 6DRepNet: The Ultimate Head Pose Estimation Model!
Features:
* State-of-the-art accuracy
* Comprehensive tools for training, testing, and inference
* Easy setup with conda
* Supports multiple datasets
Watch the performance showcase on GitHub for future advancements.
[Source Code] [Paper]
join our community:
๐ @deeplearning_ai
Features:
* State-of-the-art accuracy
* Comprehensive tools for training, testing, and inference
* Easy setup with conda
* Supports multiple datasets
Watch the performance showcase on GitHub for future advancements.
[Source Code] [Paper]
join our community:
๐ @deeplearning_ai
Data Science, Machine Learning & Artificial Intelligence Certification for FREE in 2024
Amazing new year gifts for my subscribers
๐ Free Data Science Books
๐ Machine Learning Handwritten Notes
๐ Python Free Learning Resources
๐ Learn AI with ChatGPT
๐ Build Chatbots using LLM
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๐ Free Coding Certified Courses
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Send โค๏ธ if you need more free resources
Amazing new year gifts for my subscribers
๐ Free Data Science Books
๐ Machine Learning Handwritten Notes
๐ Python Free Learning Resources
๐ Learn AI with ChatGPT
๐ Build Chatbots using LLM
๐ Learn Generative AI
๐ Free Coding Certified Courses
Join fast: ๐๐
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Send โค๏ธ if you need more free resources
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Data Science and Machine Learning
Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
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๐ข FREE TRAINING:
Navigating the Landscape of MLOps & LLMOps ๐
๐ฅ Join our FREE MLOps course demo and acquire essential skills for AI and data science across Multicloud ๐
๐ Reserve your seat now:
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๐ What you'll gain:
1๏ธโฃ ML model deployment techniques on AWS, Azure, GCP & open source.
2๏ธโฃ Efficient data management insights.
3๏ธโฃ Explore the latest MLOps tools.
4๏ธโฃ Real-time interaction with expert instructors.
๐ฉ Limited spots available! Don't miss out!
๐ Enroll now:
https://bit.ly/mlops-webinar
๐ฅ Share with fellow ML enthusiasts! ๐โจ
Navigating the Landscape of MLOps & LLMOps ๐
๐ฅ Join our FREE MLOps course demo and acquire essential skills for AI and data science across Multicloud ๐
๐ Reserve your seat now:
https://bit.ly/mlops-webinar
๐ What you'll gain:
1๏ธโฃ ML model deployment techniques on AWS, Azure, GCP & open source.
2๏ธโฃ Efficient data management insights.
3๏ธโฃ Explore the latest MLOps tools.
4๏ธโฃ Real-time interaction with expert instructors.
๐ฉ Limited spots available! Don't miss out!
๐ Enroll now:
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๐ฅ Share with fellow ML enthusiasts! ๐โจ
Forwarded from SHOHRUH
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Forwarded from Python | Machine Learning | Coding | R
This channels is for Programmers, Coders, Software Engineers.
0๏ธโฃ Python
1๏ธโฃ Data Science
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4๏ธโฃ Artificial Intelligence
5๏ธโฃ Data Analysis
6๏ธโฃ Statistics
7๏ธโฃ Deep Learning
8๏ธโฃ programming Languages
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Introducing ECoDepth: The New Benchmark in Diffusive Mono-Depth
From the labs of IITD, we unveil ECoDepth - our groundbreaking SIDE model powered by a diffusion backbone and enriched with ViT embeddings. This innovation sets a new standard in single image depth estimation (SIDE), offering unprecedented accuracy and semantic understanding.
Key Features:
โ Revolutionary MDE approach tailored for SIDE tasks
โ Enhanced semantic context via ViT embeddings
โ Superior performance in zero-shot transfer tasks
โ Surpasses previous SOTA models by up to 14%
Dive into the future of depth estimation with ECoDepth. Access our source code and explore the full potential of our model.
๐ Read the Paper
๐ป Get the Code
#ArtificialIntelligence #MachineLearning #DeepLearning #ComputerVision #AIwithPapers #Metaverse
join our community:
๐ @deeplearning_ai
From the labs of IITD, we unveil ECoDepth - our groundbreaking SIDE model powered by a diffusion backbone and enriched with ViT embeddings. This innovation sets a new standard in single image depth estimation (SIDE), offering unprecedented accuracy and semantic understanding.
Key Features:
โ Revolutionary MDE approach tailored for SIDE tasks
โ Enhanced semantic context via ViT embeddings
โ Superior performance in zero-shot transfer tasks
โ Surpasses previous SOTA models by up to 14%
Dive into the future of depth estimation with ECoDepth. Access our source code and explore the full potential of our model.
๐ Read the Paper
๐ป Get the Code
#ArtificialIntelligence #MachineLearning #DeepLearning #ComputerVision #AIwithPapers #Metaverse
join our community:
๐ @deeplearning_ai
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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
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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
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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://www.tg-me.com/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://www.tg-me.com/deeplearning_ai
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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://www.tg-me.com/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://www.tg-me.com/deeplearning_ai
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.