Want to jump ahead in artificial intelligence and/or digital pathology? Excited to share that after 2+ years of development PathML 2.0 is out! An open source #computational #pathology software library created by Dana-Farber Cancer Institute/Harvard Medical School and Weill Cornell Medicine led by Massimo Loda to lower the barrier to entry to #digitalpathology and #artificialintelligence , and streamline all #imageanalysis or #deeplearning workflows.

⭐ Code: https://github.com/Dana-Farber-AIOS/pathml

🌴🌴Direct-a-Video: driving Video Generation🌴🌴

👉Direct-a-Video is a text-to-video generation framework that allows users to individually or jointly control the camera movement and/or object motion. Authors: City University of HK, Kuaishou Tech & Tianjin.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Decoupling camera/object motion in gen-AI
✅Allowing users to independently/jointly control
✅Novel temporal cross-attention for cam motion
✅Training-free spatial cross-attention for objects
✅Driving object generation via bounding boxes

hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse

👉Channel: @MachineLearning_Programming
👉Paper https://arxiv.org/pdf/2402.03162.pdf
👉Project https://direct-a-video.github.io/

🚀 Discover LiteHPE: Advanced Head Pose Estimation 🚀

Features:
🛠️ Setup in Minutes:
📈 Top-Tier Performance:
✅ Achieve low Mean Absolute Error rates
✅ Models range from MobileOne_s0 to s4
✅ Pretrained models ready for download

🌟 🌟 Star us on GitHub for the latest updates: LiteHPE on GitHub.

Boost your project's capabilities with LiteHPE – the forefront of head pose estimation technology!

#AI #MachineLearning #HeadPoseEstimation #Technology #DeepLearning

🔗 Join now: @MachineLearning_Programming

🚀 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


#3DGazeNet #GazeEstimation #AI #DeepLearning #TechInnovation

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

🚀 PIPNet: One-Click Facial Landmark Detection 🎯

🔗 GitHub: Star ⭐ the Repo | 🎥 Watch Dem

🔥 Key Features:
✅ One-Click Inference – Just run & detect!
✅ High Accuracy (300W dataset) 📊
✅ ResNet-powered for robustness
✅ Supports training, testing & real-time demo 🎥

📌 Run Inference in One Click:
python main.py --demo

📊 Performance:
🔹 ResNet101 (120 epochs) → 3.17 NME

🌟 Support Open Source! Star ⭐ & Share!

🔗 GitHub Repo

#AI #DeepLearning #FacialRecognition #PIPNet #OneClickInference 🚀

🚀 Refactored HRNet Now Live! 🚀

🔥 Supercharge your computer vision projects with high-resolution HRNet models – fully refactored for easy training/testing!

✅ Multiple ImageNet-pretrained models
✅ Lightning-fast setup
✅ Top-tier accuracy

👉 Check it out & ⭐️ Star the repo if you find it useful!
GitHub: Shohruh72/HRNet

#AI #DeepLearning #OpenSource

✅ @MachineLearning_Programming

🎬 Live Portraits AI: Bring Photos to Life!

Transform any static portrait into a vivid animation—just one click.

✨ One-click animation
✨ Realistic facial movements
✨ Supports image & video input

👉 [Try it now!]

#AI #PortraitAnimation #DeepLearning


@MachineLearning_Programming