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🌴🌴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/
👉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/
LeGrad: Layerwise Explainability GRADient method for large ViT transformer architectures
Explore More:
💻DEMO: you may use demo
📖Read the Paper: Access Here
💻Source Code: Explore on GitHub
Relevance: #AI #machinelearning #deeplearning #computervision
join our community:
👉 @MachineLearning_Programming
Explore More:
💻DEMO: you may use demo
📖Read the Paper: Access Here
💻Source Code: Explore on GitHub
Relevance: #AI #machinelearning #deeplearning #computervision
join our community:
👉 @MachineLearning_Programming
Result.gif
23.1 MB
🚀 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!
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🔗 Join now: @MachineLearning_Programming
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!
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🔗 Join now: @MachineLearning_Programming
🚀 MLOps Market to reach US$4 Billion in 2025
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Navigating the Landscape of MLOps & LLMOps
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Unleash MLOps Mastery - FREE Training on AWS, Azure, GCP & Open-source!
Navigating the Landscape of MLOps & LLMOps
🌟 Unlock ML deployment secrets on top clouds & open source.
💡 Dive into data management insights.
🛠️ Harness the latest MLOps tools.
👥 Real-time expert interaction.
🔥 Limited spots! Enroll now:
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🚀 Share with ML enthusiasts! #MLOps #AI #TechTraining
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6.5 MB
🚀 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
Pretrained Weights:Quick start with our pretrained weights stored in the
💻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!
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!
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💼 Earn up to ₹26.6 Lakhs/Year as a Certified MLOps Engineer!
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💼 Earn up to ₹35.1 Lakhs/Year as a Certified MLOps Engineer!
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🚀 The Future of Object Detection is Here!
🔍Achieve state-of-the-art results with just one line of code! 🔥
🎥 Live Demos & Code: GitHub Repo
📥 Pretrained Models: Ready for download—plug and play!
⭐️ Support innovation! Star the repo now 👉 GitHub Link
📢 Join our ML community: @MachineLearning_Programming
#MachineLearning #AI #ObjectDetection #YOLO #OpenSource #DevCommunity #TechInnovation
🔍Achieve state-of-the-art results with just one line of code! 🔥
🎥 Live Demos & Code: GitHub Repo
📥 Pretrained Models: Ready for download—plug and play!
⭐️ Support innovation! Star the repo now 👉 GitHub Link
📢 Join our ML community: @MachineLearning_Programming
#MachineLearning #AI #ObjectDetection #YOLO #OpenSource #DevCommunity #TechInnovation
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🚀 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 🚀
🔗 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 🚀
🧠 VGGT: Visual Geometry Grounded Transformer
⚡️ Fast, accurate 3D scene understanding from just a few images — no post-processing needed!
🎯 Outputs: camera pose, depth, point cloud & 3D tracking
🔥 Boosts tasks like view synthesis & non-rigid tracking
📄 Read the paper
💻 Code on GitHub
#AI #3D #Transformer #VGGT #ComputerVision
✅ @MachineLearning_Programming
⚡️ Fast, accurate 3D scene understanding from just a few images — no post-processing needed!
🎯 Outputs: camera pose, depth, point cloud & 3D tracking
🔥 Boosts tasks like view synthesis & non-rigid tracking
📄 Read the paper
💻 Code on GitHub
#AI #3D #Transformer #VGGT #ComputerVision
✅ @MachineLearning_Programming
🚨 FREE MLOps TRAINING ALERT 🚨
💼 Earn up to ₹35.1 Lakhs/Year as a Certified MLOps Engineer!
🚀 Master MLOps & LLMOps on AWS, Azure, GCP, and Open-Source Tools!
🔥 LIMITED SPOTS – Act Fast!
📝 Secure Your Spot Now:
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💡 Transform Your Career with our Expert Training!
🎯 Share with fellow ML Enthusiasts and future tech leaders!
#MLOps #AI #TechCareers #FreeTraining
💼 Earn up to ₹35.1 Lakhs/Year as a Certified MLOps Engineer!
🚀 Master MLOps & LLMOps on AWS, Azure, GCP, and Open-Source Tools!
🔥 LIMITED SPOTS – Act Fast!
📝 Secure Your Spot Now:
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💡 Transform Your Career with our Expert Training!
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#MLOps #AI #TechCareers #FreeTraining