We lifted 2 functions out of this paper's own repositories and ran 2 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| jiahuilei/mosca | canonical | 2 of 2 |
| Function | Status | Where it lives |
|---|---|---|
| resample_curve | Ran | jiahuilei/mosca/lib_mosca/mosca.py code served (permissive licence) · get_code("1cd96312c2e6f47b") |
| robust_curve_dist_kernel | Ran | jiahuilei/mosca/lib_mosca/mosca.py code served (permissive licence) · get_code("1943453b55e4a593") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
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.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2405.17421")
get_code_for_paper("2405.17421")
have("2405.17421")
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