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MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffolds

About

We introduce 4D Motion Scaffolds (MoSca), a modern 4D reconstruction system designed to reconstruct and synthesize novel views of dynamic scenes from monocular videos captured casually in the wild. To address such a challenging and ill-posed inverse problem, we leverage prior knowledge from foundational vision models and lift the video data to a novel Motion Scaffold (MoSca) representation, which compactly and smoothly encodes the underlying motions/deformations. The scene geometry and appearance are then disentangled from the deformation field and are encoded by globally fusing the Gaussians anchored onto the MoSca and optimized via Gaussian Splatting. Additionally, camera focal length and poses can be solved using bundle adjustment without the need of any other pose estimation tools. Experiments demonstrate state-of-the-art performance on dynamic rendering benchmarks and its effectiveness on real videos.

Jiahui Lei, Yijia Weng, Adam Harley, Leonidas Guibas, Kostas Daniilidis• 2024

Related benchmarks

TaskDatasetResultRank
Novel View SynthesisiPhone DyCheck 7 scenes 2x resolution
mPSNR19.32
31
Novel View SynthesisiPhone dataset
SSIM0.706
23
4D ReconstructionDyCheck (test)
mPSNR19.54
21
Dynamic Scene Novel View SynthesisNVIDIA video dataset average over all scenes 112
PSNR26.72
17
Novel View SynthesisDyCheck (test)
mPSNR18.24
15
Dynamic Scene ReconstructionNVIDIA-LS (test)
PSNR23.72
10
Camera pose estimationSintel (test)
ATE0.09
9
Novel View SynthesisNVIDIA dataset (test)
Mean PSNR21.45
9
Correspondence TrackingDyCheck (test)
PCK-T82.4
8
Novel View SynthesisDyCheck 12 (test)
Apple PSNR19.4
7
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