4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous
  Capture
Reconstructing fast-dynamic scenes from multi-view videos is crucial for
high-speed motion analysis and realistic 4D reconstruction. However, the
majority of 4D capture systems are limited to frame rates below 30 FPS (frames
per second), and a direct 4D reconstruction of high-speed motion from low FPS
input may lead to undesirable results. In this work, we propose a high-speed 4D
capturing system only using low FPS cameras, through novel capturing and
processing modules. On the capturing side, we propose an asynchronous capture
scheme that increases the effective frame rate by staggering the start times of
cameras. By grouping cameras and leveraging a base frame rate of 25 FPS, our
method achieves an equivalent frame rate of 100-200 FPS without requiring
specialized high-speed cameras. On processing side, we also propose a novel
generative model to fix artifacts caused by 4D sparse-view reconstruction, as
asynchrony reduces the number of viewpoints at each timestamp. Specifically, we
propose to train a video-diffusion-based artifact-fix model for sparse 4D
reconstruction, which refines missing details, maintains temporal consistency,
and improves overall reconstruction quality. Experimental results demonstrate
that our method significantly enhances high-speed 4D reconstruction compared to
synchronous capture.
686c928b364e2ad167eb53f1
Yutian Chen
claimed_verified
2025-07-13T07:34:00.273Z
662d01a7f5f38dec890a2962
/avatars/34463ea787d4c543791c5207598650f2.svg
Yutian Chen
user
yutian05
686c928b364e2ad167eb53f2
Shi Guo
686c928b364e2ad167eb53f3
Tianshuo Yang
claimed_verified
2025-07-13T07:29:47.793Z
657010abf2c1c863093941cb
/avatars/25b8a1ecdea3b5ab687dc8331b5f8615.svg
Tianshuo
user
Violin-Y
686c928b364e2ad167eb53f4
Lihe Ding
admin_assigned
2025-07-08T13:54:46.672Z
64190a6c0956be7233a5f317
/avatars/8590515089bc31a168bc2da2c7516dfb.svg
Lihe Ding
user
Lihe
686c928b364e2ad167eb53f5
Xiuyuan Yu
admin_assigned
2025-07-08T13:54:12.085Z
683277563a242c5e2d76a2ef
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/kRcqg3Qwh2MYu1ePLulnp.png
Xiuyuan Yu
user
edward1145
686c928b364e2ad167eb53f6
Jinwei Gu
admin_assigned
2025-07-08T13:54:28.245Z
647e8118770c299e56fc2bc8
/avatars/adf80f3473dda42450148789ae5c208f.svg
Jinwei Gu
user
jwgu
686c928b364e2ad167eb53f7
Tianfan Xue
admin_assigned
2025-07-08T13:54:19.731Z
67631f57abfbd60470d4b3c3
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/5VrG0IZjYrDLiatOr4y06.png
Tianfan Xue
user
littlemouse9
4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous
  Capture
Reconstructing fast-dynamic scenes from multi-view videos is crucial for
high-speed motion analysis and realistic 4D reconstruction. However, the
majority of 4D capture systems are limited to frame rates below 30 FPS (frames
per second), and a direct 4D reconstruction of high-speed motion from low FPS
input may lead to undesirable results. In this work, we propose a high-speed 4D
capturing system only using low FPS cameras, through novel capturing and
processing modules. On the capturing side, we propose an asynchronous capture
scheme that increases the effective frame rate by staggering the start times of
cameras. By grouping cameras and leveraging a base frame rate of 25 FPS, our
method achieves an equivalent frame rate of 100-200 FPS without requiring
specialized high-speed cameras. On processing side, we also propose a novel
generative model to fix artifacts caused by 4D sparse-view reconstruction, as
asynchrony reduces the number of viewpoints at each timestamp. Specifically, we
propose to train a video-diffusion-based artifact-fix model for sparse 4D
reconstruction, which refines missing details, maintains temporal consistency,
and improves overall reconstruction quality. Experimental results demonstrate
that our method significantly enhances high-speed 4D reconstruction compared to
synchronous capture.
A novel capturing and processing system using low FPS cameras and a video-diffusion-based generative model enhances high-speed 4D reconstruction.
asynchronous capture video-diffusion-based artifact-fix model sparse 4D reconstruction temporal consistency