TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos
  via Diffusion Models
We present TrajectoryCrafter, a novel approach to redirect camera
trajectories for monocular videos. By disentangling deterministic view
transformations from stochastic content generation, our method achieves precise
control over user-specified camera trajectories. We propose a novel dual-stream
conditional video diffusion model that concurrently integrates point cloud
renders and source videos as conditions, ensuring accurate view transformations
and coherent 4D content generation. Instead of leveraging scarce multi-view
videos, we curate a hybrid training dataset combining web-scale monocular
videos with static multi-view datasets, by our innovative double-reprojection
strategy, significantly fostering robust generalization across diverse scenes.
Extensive evaluations on multi-view and large-scale monocular videos
demonstrate the superior performance of our method.
67ce8388764226f050ad18b3
Mark YU
67ce8388764226f050ad18b4
Wenbo Hu
claimed_verified
2025-03-10T08:00:42.681Z
657a7458afbb0117ba15c59f
https://cdn-avatars.huggingface.co/v1/production/uploads/657a7458afbb0117ba15c59f/8_iwTS1UG_mKnfylFbLsY.jpeg
Wenbo Hu
user
wbhu-tc
67ce8388764226f050ad18b5
Jinbo Xing
claimed_verified
2025-03-10T08:00:40.328Z
64770e86d7cf39f2e937ae9a
https://cdn-avatars.huggingface.co/v1/production/uploads/64770e86d7cf39f2e937ae9a/pLqGg2z1KzQxCGpMwds-9.jpeg
Jinbo Xing
user
Doubiiu
67ce8388764226f050ad18b6
Ying Shan
admin_assigned
2025-03-10T10:06:56.510Z
63ca3ddc04c979828310bfcb
/avatars/615e0d8622950b4408b40d550f02a894.svg
Ying Shan
user
yshan2u
TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos
  via Diffusion Models
We present TrajectoryCrafter, a novel approach to redirect camera
trajectories for monocular videos. By disentangling deterministic view
transformations from stochastic content generation, our method achieves precise
control over user-specified camera trajectories. We propose a novel dual-stream
conditional video diffusion model that concurrently integrates point cloud
renders and source videos as conditions, ensuring accurate view transformations
and coherent 4D content generation. Instead of leveraging scarce multi-view
videos, we curate a hybrid training dataset combining web-scale monocular
videos with static multi-view datasets, by our innovative double-reprojection
strategy, significantly fostering robust generalization across diverse scenes.
Extensive evaluations on multi-view and large-scale monocular videos
demonstrate the superior performance of our method.
TrajectoryCrafter uses a dual-stream conditional video diffusion model to precisely redirect camera trajectories in monocular videos by integrating point cloud renders and source videos.
dual-stream conditional video diffusion model point cloud renders camera trajectories monocular videos stochastic content generation deterministic view transformations web-scale monocular videos static multi-view datasets double-reprojection strategy robust generalization