TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos via Diffusion Models
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
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.
Key facts. Cited by 125 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 97 of its 103 references that are in the map. First posted on arXiv 7 Mar 2025.
Builds on
97 of 103 references.
Closest ancestors · 15
Same direction, newest first
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- 2024StereoCrafter: Diffusion-based Generation of Long and High-fidelity Stereoscopic 3D from Monocular Videos11 Sep
- 2024ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis3 Sep
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- 2024MultiDiff: Consistent Novel View Synthesis from a Single Image26 Jun
- 2024NVS-Solver: Video Diffusion Model as Zero-Shot Novel View Synthesizer24 May
- 2024CAT3D: Create Anything in 3D with Multi-View Diffusion Models16 May
3 more
Other references · 82
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 2020Denoising Diffusion Implicit Modelscited by 9,781
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- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
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- 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,584
- 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,567
- 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,556
- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,476
- 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
- 2024Depth Anything V2cited by 1,422
- 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
- 2024Grounding Image Matching in 3D with MASt3Rcited by 983
- 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 957
- 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 751
- 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
- 2021MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereocited by 740
- 2023Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fieldscited by 671
- 2023Mip-Splatting: Alias-free 3D Gaussian Splattingcited by 667
- 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 642
- 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
- 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 580
- 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 575
- 2024MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Imagescited by 566
- 2023DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Visioncited by 537
- 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generationcited by 535
- 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 511
- 2023Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splattingcited by 476
- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 471
- 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 471
- 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 460
- 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 442
- 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
- 2024Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teacherscited by 393
- 2022Kubric: A scalable dataset generatorcited by 381
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- 2024Open-Sora Plan: Open-Source Large Video Generation Modelcited by 296
- 2022Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activitiescited by 287
- 2023FSGS: Real-Time Few-shot View Synthesis using Gaussian Splattingcited by 279
50 most cited of 82 All 82 (JSON)
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Citing papers per year: 2025: 38; 2026: 87.
125 papers.
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