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Melon: Reconstructing 3d Objects from Images With Unknown Poses

Google Research 3:01 am on May 23, 2024

MELON is a neural field-based approach for inferring camera poses in NeRF synthetic datasets without requiring initial pose guesses, achieving competitive PSNR and novel view generation from noisy images. It enhances existing methods with efficiency and robustness. MELON's application extends beyond theoretical demonstration to potential real-world adaptation.

Introduction of MELON: Neural field-based approach for camera pose inference.
Pose Estimation Improvement: Achieves competitive PSNR without initial pose guesses.
Novel View Synthesis from Noise: Effective reconstruction from noisy, unposed images.
Real-World Applications Potential: Adaptation for real-world conditions discussed.
Contribution to NeRF Synthetic Dataset Analysis: Comparative performance evaluation with ground truth and other models.

http://blog.research.google/2024/03/melon-reconstructing-3d-objects-from.html

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Melon: Reconstructing 3d Objects from Images With Unknown Poses

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