REVIEW 8 cited by
Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstruction
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
We introduce Geo4D, a method to repurpose video diffusion models for monocular 3D reconstruction of dynamic scenes. By leveraging the strong dynamic priors captured by large-scale pre-trained video models, Geo4D can be trained using only synthetic data while generalizing well to real data in a zero-shot manner. Geo4D predicts several complementary geometric modalities, namely point, disparity, and ray maps. We propose a new multi-modal alignment algorithm to align and fuse these modalities, as well as a sliding window approach at inference time, thus enabling robust and accurate 4D reconstruction of long videos. Extensive experiments across multiple benchmarks show that Geo4D significantly surpasses state-of-the-art video depth estimation methods.
Forward citations
Cited by 8 Pith papers
-
AniGS: Bridging Rendering and Diffusion Prior for 3D Scene Animation
AniGS animates a static 3D Gaussian Splatting scene by iteratively distilling video-diffusion motion into a time-conditioned deformation field while keeping static regions fixed.
-
Video Generation Models are General-Purpose Vision Learners
A video-diffusion backbone fine-tuned as a single-step multi-task perceiver matches or beats specialists on depth, normals, pose and segmentation, with high data efficiency and sim-to-real transfer.
-
Epipolar Geometry Improves Video Generation Models
Ranking generated videos by their epipolar (Sampson) error and fine-tuning Wan2.1 with Flow-DPO cuts epipolar error 31% and raises human-rated 3D consistency from 54% to 72%.
-
PAGE-4D: Disentangled pose and geometry estimation for vggt-4d perception
PAGE-4D is a feedforward extension of VGGT that uses a dynamics-aware aggregator and mask to disentangle pose estimation from geometry reconstruction in videos with moving objects.
-
Mem4D: Decoupling Static and Dynamic Memory for Dynamic Scene Reconstruction
Mem4D decouples static and dynamic memory to improve online monocular 3D reconstruction of dynamic scenes, showing metric-depth gains on Sintel and Bonn but worse static reconstruction than CUT3R.
-
Geometry-Aware Single-Image 4D Synthesis via Dense Trajectory Generation
A diffusion model generates dense 4D point trajectories from a single image, and a separate view-synthesis module renders them into novel-view videos.
-
Advances in 4D Representation: Geometry, Motion, and Interaction
A representation-centric survey of 4D generation and reconstruction, organized by geometry, motion, and interaction, with qualitative trade-off comparisons across seven representation families.
-
Reconstructing 4D Spatial Intelligence: A Survey
A review that classifies 4D scene reconstruction methods into five progressive levels: low-level cues, scene components, dynamic scenes, interactions, and physics.
Discussion (0). Continue with ORCID to comment.