🔍 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.

👀 Live Demo:
Visualize the power of L2CS-Net with your own video:


🌟 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!

🔗 GitHub Repository

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

Key Features:
🔹 Advanced Neural Network: Built on the robust U2-Net architecture.
🔹 Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
🔹 Seamless Integration: Train, test, and visualize with simple commands.

Demo Visualization:Visualize the demo by configuring your video path in main.py and showcasing the power of 3DGazeNet.

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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Join us in pushing the boundaries of gaze estimation technology with 3DGazeNet!

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🚀 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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🚀 3DGazeNet: Next-Gen Gaze Estimation! - get instant results with just one click.

Discover how to train powerful gaze estimation models using only synthetic data and weak supervision—no huge real-world datasets needed.
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