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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:

✅Revolutionary MDE approach tailored for SIDE tasks
✅Enhanced semantic context via ViT embeddings
✅Superior performance in zero-shot transfer tasks
✅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.

📖 Read the Paper
💻 Get the Code

#ArtificialIntelligence #MachineLearning #DeepLearning #ComputerVision #AIwithPapers #Metaverse

join our community:
👉 @deeplearning_ai

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:

✅Novel approach for modeling clothed human figures.
✅Unified framework accommodating various clothing types.
✅Consistent representation of both body and clothing.
✅Enables seamless modification of identity, shape, clothing, and pose.
✅Extensive dataset with detailed clothing information.

Explore More:
💻Project Details: Discover More
📖Read the Paper: Access Here
💻Source Code: Explore on GitHub

Relevance: #artificialintelligence #machinelearning #AI #deeplearning #computervision

join our community:
👉 @deeplearning_ai

🛞 6Img-to-3D driving scenarios 🛞

👮‍♀️ EPFL (+ Continental) unveils 6Img-to-3D, novel transformer-based encoder-renderer method to create 3D onbounded outdoor driving scenarios with only six pics

🥺 Review: https://shorturl.at/dZ018

🤨 Paper: arxiv.org/pdf/2404.12378.pdf

👉 Project: 6img-to-3d.github.io/

👉 Code: github.com/continental/6Img-to-3D

✅ https://t.iss.one/deeplearning_ai

🔍 Introducing UniRef++: Advanced Object Segmentation in Spatial and Temporal Domains
🚀 Key Features:

Unified Model: UniRef++ seamlessly handles segmentation tasks:
✅Referring Image Segmentation (RIS)
✅Few-Shot Segmentation (FSS)
✅Referring Video Object Segmentation (RVOS)
✅Video Object Segmentation (VOS)

Core Component: UniFusion module
✅Integrates reference information efficiently
✅Utilizes flash attention for high efficiency

Compatibility: Acts as a plug-in for foundational models like SAM

🌐 UniRef++ is the official extended implementation from ICCV 2023's UniRef.

Stay tuned for more updates!

👉 Code: https://github.com/FoundationVision/UniRef
🤨 Paper: [Paper link]

✅ https://t.iss.one/deeplearning_ai

India's Largest Free Webinar on LLMs especially focused on the recently released LLAMA-3 by Meta.

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🚀 Explore SCRFD: High-Efficiency, High-Accuracy Face Detection 🚀


Unlock next-level face detection capabilities with SCRFD – efficiency and accuracy in one solution!


📈 Performance at a Glance:

✅Model range: SCRFD_500M to SCRFD_34G
✅Accuracy up to 96.06%
✅Inference as fast as 3.6 ms

🔍 Explore more and consider starring our repo for updates:
--- GitHub Repository.
--- Paper



#AI #MachineLearning #FaceDetection #TechInnovation #DeepLearning

✅ https://t.iss.one/deeplearning_ai

🔍 Discover the Power of Fine-Grained Gaze Estimation with L2CS-Net! 🌟

🚀 Key Features:
✅Advanced Architecture: Built using state-of-the-art neural network structures.
✅Versatile Utilities: Packed with utility functions and classes for seamless integration.
✅Robust Data Handling: Efficient data loading, preprocessing, and augmentation.
✅Comprehensive Training & Testing: Easy-to-follow scripts for training and testing your models.

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Star our repo on GitHub and be part of the innovative community pushing the boundaries of gaze estimation. Your support drives us forward!

🔗 GitHub Repository

Let's advance gaze estimation together! 🚀🌐 #GazeEstimation #DeepLearning #AI #MachineLearning #ComputerVision

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🚀 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!

🌟 Key Features:

* Real-time face detection with ONNX models.
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* Live visualization of emotion scores.

⭐️ Star our repo and elevate your AI projects: Emotion Recognition on GitHub


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✅ https://github.com/Shohruh72

✅ https://t.iss.one/deeplearning_ai

🌟 Join Our Team as a Senior Data Researcher at Wunder Fund! 🌟

🚀 Location: Remote/Relocation to various countries
💸 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.

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- Train models, test hypotheses, and achieve maximum model accuracy
- Work with top-tier programmers, mathematicians, and physicists

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- Proficiency in Python and Mathematics
- Experience with Kaggle (Master/Grandmaster)
- Success in training transformers and LSTM

🌐 Learn More & Apply

Are you struggling with invoking functions, passing arguments, or handling return values in Large Language Models (LLMs)?

Whether you’re a seasoned developer or just starting your journey in Gen AI.

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1. Introduction to LLMs.
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🗓 Date: 14th June, Friday
⏰ Time: 9 PM, IST
🔗 Link : https://www.buildfastwithai.com/events/function-calling-with-llms

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:
💻Source Code: Explore on GitHub
💻Project Details: Discover More
📖Read the Paper: Access Here


✅ https://t.iss.one/deeplearning_ai