✨Generative Video Motion Editing with 3D Point Tracks

📝 Summary:
This paper presents a track-conditioned video-to-video framework for precise joint camera and object motion editing. It uses 3D point tracks to maintain spatiotemporal coherence and handle occlusions through explicit depth cues. This enables diverse motion edits.

🔹 Publication Date: Published on Dec 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02015
• PDF: https://arxiv.org/pdf/2512.02015
• Project Page: https://edit-by-track.github.io/

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✓ https://xn--r1a.website/DataScienceT

#VideoEditing #GenerativeAI #ComputerVision #3DTracking #DeepLearning

✨SpectralSplats: Robust Differentiable Tracking via Spectral Moment Supervision

📝 Summary:
SpectralSplats resolves vanishing gradients in 3D Gaussian Splatting tracking by optimizing in the frequency domain using spectral moments. This creates a global gradient basin of attraction, ensuring robust tracking even with severe misalignment. A frequency annealing schedule guides precise ali...

🔹 Publication Date: Published on Mar 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.24036
• PDF: https://arxiv.org/pdf/2603.24036
• Project Page: https://avigailco.github.io/SpectralSplats/

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For more data science resources:
✓ https://xn--r1a.website/DataScienceT

#3DTracking #GaussianSplatting #ComputerVision #Optimization #DifferentiableRendering