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Vid-CamEdit: Video Camera Trajectory Editing with Generative Rendering from Estimated Geometry

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arxiv 2506.13697 v1 pith:CRK3OIJ2 submitted 2025-06-16 cs.CV

Vid-CamEdit: Video Camera Trajectory Editing with Generative Rendering from Estimated Geometry

classification cs.CV
keywords cameragenerativegeometryvideodatanoveltrajectoryvideos
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challenging due to its ill-posed nature and the limited multi-view video data for training. Traditional reconstruction methods struggle with extreme trajectory changes, and existing generative models for dynamic novel view synthesis cannot handle in-the-wild videos. Our approach consists of two steps: estimating temporally consistent geometry, and generative rendering guided by this geometry. By integrating geometric priors, the generative model focuses on synthesizing realistic details where the estimated geometry is uncertain. We eliminate the need for extensive 4D training data through a factorized fine-tuning framework that separately trains spatial and temporal components using multi-view image and video data. Our method outperforms baselines in producing plausible videos from novel camera trajectories, especially in extreme extrapolation scenarios on real-world footage.

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. $h$-control: Training-Free Camera Control via Block-Conditional Gibbs Refinement

    cs.CV 2026-05 unverdicted novelty 7.0

    h-control introduces block-conditional pseudo-Gibbs refinement for training-free camera control in flow-matching video generators, achieving superior FVD scores on RealEstate10K and DAVIS benchmarks.

  2. CameraAnything: Refilming Videos with Arbitrary Camera Control

    cs.CV 2026-07 conditional novelty 6.0

    A video diffusion editor jointly controls extrinsic pose, multi-shot cuts, focal length, and native resolution via Plücker rays in resolution-aware 3D RoPE, trained on synthetic multi-camera pairs.

  3. TriMotion: Modality-Agnostic Camera Control for Video Generation

    cs.CV 2026-06 unverdicted novelty 6.0

    TriMotion is a modality-agnostic framework that maps video, pose, and text descriptions of the same camera trajectory into a shared motion embedding space, trained with a new triplet dataset and latent consistency obj...

  4. $h$-control: Training-Free Camera Control via Block-Conditional Gibbs Refinement

    cs.CV 2026-05 unverdicted novelty 6.0

    h-control augments hard-replacement guidance with block-conditional pseudo-Gibbs refinement on unobserved latent sites and adaptive 3D patch freezing to achieve superior FVD on RealEstate10K and DAVIS.