title: TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos
    via Diffusion Models
summary: 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.
paper_authors._id: 67ce8388764226f050ad18b3
paper_authors.name: Mark YU
paper_authors._id: 67ce8388764226f050ad18b4
paper_authors.name: Wenbo Hu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-03-10T08:00:42.681Z
paper_authors._id: 657a7458afbb0117ba15c59f
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/657a7458afbb0117ba15c59f/8_iwTS1UG_mKnfylFbLsY.jpeg
paper_authors.fullname: Wenbo Hu
paper_authors.type: user
paper_authors.user: wbhu-tc
paper_authors._id: 67ce8388764226f050ad18b5
paper_authors.name: Jinbo Xing
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-03-10T08:00:40.328Z
paper_authors._id: 64770e86d7cf39f2e937ae9a
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/64770e86d7cf39f2e937ae9a/pLqGg2z1KzQxCGpMwds-9.jpeg
paper_authors.fullname: Jinbo Xing
paper_authors.type: user
paper_authors.user: Doubiiu
paper_authors._id: 67ce8388764226f050ad18b6
paper_authors.name: Ying Shan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-10T10:06:56.510Z
paper_authors._id: 63ca3ddc04c979828310bfcb
paper_authors.avatarUrl: /avatars/615e0d8622950b4408b40d550f02a894.svg
paper_authors.fullname: Ying Shan
paper_authors.type: user
paper_authors.user: yshan2u
paper_title: TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos
    via Diffusion Models
paper_summary: 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.
paper_ai_keywords: dual-stream conditional video diffusion model point cloud renders source videos deterministic view transformations stochastic content generation double-reprojection strategy