Hugging Face Trending Papers
Any3R: Feedforward 3D Reconstruction from Any Camera Type
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arXiv Computer Vision
Oct 28
Any3R: Feedforward 3D Reconstruction from Any Camera Type
Any3R is a feed‑forward 3D reconstruction model that works with any central camera type, regardless of lens distortion or field‑of‑view limits. It conditions on a dense ray field—unit direction vectors through every pixel—so its positional encoding and loss function are lens‑agnostic. Evaluated on thirteen camera types across three datasets, Any3R consistently outperforms other methods, enabling scalable reconstruction from heterogeneous, crowdsourced imagery.
arXiv Computer Vision
Oct 23
OmniRay: Camera-Agnostic Monocular 3D Reconstruction with Composite Ray Fields
OmniRay is a feed‑forward model for monocular 3D reconstruction that works without assuming a pinhole camera. It predicts a ray direction and a scale‑free radial distance for each pixel using a composite Ray Module consisting of a monotone radial base, a spherical‑harmonic residual, and a free‑form residual. Experiments across various camera types show that OmniRay achieves state‑of‑the‑art performance in camera‑agnostic monocular 3D reconstruction.
Hugging Face Trending Papers
Sep 14
G-ray: Ray-Level Relative Geometric Position Encoding in Multi-View Vision Transformers under Camera Heterogeneity
We study relative position encoding for multi-view vision Transformers under camera heterogeneity, including varying fields of view (FoVs) or projection models. Existing rotary relative position encod...
arXiv Computer Vision
Sep 15
G-ray: Ray-Level Relative Geometric Position Encoding in Multi-View Vision Transformers under Camera Heterogeneity
The paper introduces G-ray, a ray-level relative position encoding for multi-view vision Transformers that remains consistent across different camera projections. By parameterizing rotary phases with camera-local ray angles, G-ray achieves projection-invariant positional consistency and can be integrated with existing encodings without extra learned parameters. Experiments on 3D reconstruction and novel-view synthesis benchmarks show that G-ray improves performance, notably reducing mean pointmap relative error by 45.8% over MapAnything.
arXiv Computer Vision
Oct 23
HiP3R: Hierarchical Pose Graphs for Long-Horizon 3D Reconstruction
HiP3R introduces a hierarchical pose graph approach for long‑horizon 3D reconstruction, addressing the trade‑off between chunk‑level and frame‑level optimization. It first builds a robust chunk‑level Sim(3) graph to set the global layout and scale, then fixes this layout while estimating a single SE(3) camera pose per frame to merge overlapping predictions into a unified trajectory. Experiments on multiple benchmarks show that HiP3R improves camera trajectories and 3D reconstruction quality for both chunk‑based and streaming backends without extra training.
arXiv Computer Vision
Sep 15
RIGOR: Rig-Informed Geometry for Omnidirectional Reconstruction
arXiv:2609.13504v1 Announce Type: new Abstract: Recent developments in feed-forward 3D reconstruction resulted in models which can recover dense scene representations and camera motion solely from an...