🔥 Shanghai AI Lab Introduces RTMW: Real-Time Multi-Person Whole-Body Pose Estimation 🔥


• Blazing Speed: 940+ FPS on GPU, 50–300+ FPS on CPU
• High-Performance Models: Supports 2D/3D whole-body pose estimation
• Cutting-Edge Architecture: Built upon RTMPose with FPN & HEM
• Wide Dataset Coverage: Manually aligned keypoints across 14 open datasets
• Extensive Framework Support: ONNX, TensorRT, ncnn, and OpenVINO
• Open Source: Code and pre-trained models available

🔗 Discover More:
* Source code: Github
* Paper: Read the paper

✅ https://t.me/deeplearning_ai

⚽ FIFA World Cup 3D Human Pose Dataset ⚽

Discover WorldPose: a cutting-edge dataset for multi-person global pose estimation, featuring footage from the 2022 FIFA World Cup with 2.5M+ annotations!

Key Highlights:
✅ Authors: ETH, FIFA, Microsoft
✅ 150K+ frames, 2.5M+ 3D poses (SMPL format)
✅ Calibrated moving cameras & accurate trajectories

📄 Paper: arxiv.org/pdf/2501.02771
📊 Dataset: Access here

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🚀 The Future of Object Detection is Here!

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🎥 Live Demos & Code: GitHub Repo

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🌟  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]

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🚀 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! 🌟

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🔹 Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
🔹 Seamless Integration: Train, test, and visualize with simple commands.

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Pretrained Weights:Quick start with our pretrained weights stored in the weights folder.

💻Source Code: https://github.com/Shohruh72/3DGazeNet
📖Read the Paper: Access Here


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Pippo: High-Resolution Multi-View Humans from a Single Image

🔗 Discover More:
* Source code: Github
* Paper: Read the paper
* Jump to Visual: LINK

🚀 Introducing L2CS-Net: Fine-Grained Gaze Estimation 👀✨

🔗 GitHub Repo: Star ⭐ the Repo

🔥 Key Features:
✅ Fine-grained gaze estimation with deep learning
✅ Supports Gaze360 dataset
✅ Train with Single-GPU / Multi-GPU
✅ Demo for real-time visualization

📌 Quick Start:
🗂️ Prepare dataset
🏋️ Train (python main.py --train)
🎥 Video Infernece (python main.py --demo)

🌟 Support Open Source! Star ⭐ & Share!
🔗 GitHub Repo: L2CSNet

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