❇️ Creating an AI that Knows When You’re Eating Without Seeing or Hearing 🍽👀


https://github.com/ZSturman/Hows-My-Eating


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❇️ BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

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* Source Code: GitHub
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* Paper: Read the paper

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"DARTH: Holistic Test-time Adaptation for Multiple Object Tracking"

🔗 Discover More:
* Source Code: GitHub


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❇️ 3D Reconstruction with Spatial Memory


🔗 Discover More:
* Source Code: GitHub
* Project Page: Spann3R
* Supplement Video: Try it here
* Paper: Read the paper

✅ https://t.iss.one/deeplearning_ai

🔗 Discover More:
* Source Code: GitHub
* Try Demo: Try it here


✅ https://t.iss.one/deeplearning_ai

Are you an avid traveler? 🧳✈️

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❇️ AniGS: Animatable Gaussian Avatar from a Single Image with Inconsistent Gaussian Reconstruction 🔥


🔗 Discover More:
* Github Link
* Project Page: AniGS
* Paper: Read the paper

✅ https://t.iss.one/deeplearning_ai

HunyuanVideo: A Systematic Framework For Large Video Generation Model


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

✅ https://t.iss.one/deeplearning_ai

PanoDreamer: 3D Panorama Synthesis from a Single Image

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* Source code: Github
* Project Page: PanoDreamer
* Paper: Read the paper
* YouTube: Video Results

✅ https://t.iss.one/deeplearning_ai

Elevating Flow-Guided Video Inpainting with Reference Generation

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* Source code: Github
* Paper: Read the paper

✅ https://t.iss.one/deeplearning_ai

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OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving

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* Source code: Github
* Paper: Read the paper

✅ https://t.iss.one/deeplearning_ai

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


• Blazing Speed: 940+ FPS on GPU, 50–300+ FPS on CPU
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• 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.iss.one/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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