4 citations · 10 across the 11 of their papers we have counts for
16 papers
Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction
Ahan Shabanov, Peter Hedman, Ethan Weber +10
We present Free-Range Gaussians, a multi-view reconstruction method that predicts non-pixel, non-voxel-aligned 3D Gaussians from as few as four images. This is done through flow ma…
LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows
Zhengqin Li, Cheng Zhang, Jakob Engel +1
We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction. Although recent object-centric feed-forw…
ShapeR: Robust Conditional 3D Shape Generation from Casual Captures
Yawar Siddiqui, Duncan Frost, Samir Aroudj +9
Recent advances in 3D shape generation have achieved impressive results, but most existing methods rely on clean, unoccluded, and well-segmented inputs. Such conditions are rarely…
ART: Articulated Reconstruction Transformer
Zizhang Li, Cheng Zhang, Zhengqin Li +7
We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated objects from only sparse, multi-state…
DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
Chieh Hubert Lin, Zhaoyang Lv, Songyin Wu +11
We introduce the Deformable Gaussian Splats Large Reconstruction Model (DGS-LRM), the first feed-forward method predicting deformable 3D Gaussian splats from a monocular posed vide…
4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos
Zhen Xu, Zhengqin Li, Zhao Dong +3
We propose 4DGT, a 4D Gaussian-based Transformer model for dynamic scene reconstruction, trained entirely on real-world monocular posed videos. Using 4D Gaussian as an inductive bi…
Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset
Zhao Dong, Ka Chen, Zhaoyang Lv +14
We introduce the Digital Twin Catalog (DTC), a new large-scale photorealistic 3D object digital twin dataset. A digital twin of a 3D object is a highly detailed, virtually indistin…
Monocular Online Reconstruction with Enhanced Detail Preservation
Songyin Wu, Zhaoyang Lv, Yufeng Zhu +6
We propose an online 3D Gaussian-based dense mapping framework for photorealistic details reconstruction from a monocular image stream. Our approach addresses two key challenges in…
LIRM: Large Inverse Rendering Model for Progressive Reconstruction of Shape, Materials and View-dependent Radiance Fields
Zhengqin Li, Dilin Wang, Ka Chen +11
We present Large Inverse Rendering Model (LIRM), a transformer architecture that jointly reconstructs high-quality shape, materials, and radiance fields with view-dependent effects…
3D Mesh Editing using Masked LRMs
Will Gao, Dilin Wang, Yuchen Fan +6
We present a novel approach to shape editing, building on recent progress in 3D reconstruction from multi-view images. We formulate shape editing as a conditional reconstruction pr…
NeRF Analogies: Example-Based Visual Attribute Transfer for NeRFs
Michael Fischer, Zhengqin Li, Thu Nguyen-Phuoc +4
A Neural Radiance Field (NeRF) encodes the specific relation of 3D geometry and appearance of a scene. We here ask the question whether we can transfer the appearance from a source…
ReplaceAnything3D:Text-Guided 3D Scene Editing with Compositional Neural Radiance Fields
Edward Bartrum, Thu Nguyen-Phuoc, Chris Xie +5
We introduce ReplaceAnything3D model (RAM3D), a novel text-guided 3D scene editing method that enables the replacement of specific objects within a scene. Given multi-view images o…
TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusion
Yu-Ying Yeh, Jia-Bin Huang, Changil Kim +8
We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across ar…
IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images
Chih-Hao Lin, Jia-Bin Huang, Zhengqin Li +7
Inverse rendering seeks to recover 3D geometry, surface material, and lighting from captured images, enabling advanced applications such as novel-view synthesis, relighting, and vi…
GauFRe: Gaussian Deformation Fields for Real-time Dynamic Novel View Synthesis
Yiqing Liang, Numair Khan, Zhengqin Li +4
We propose a method that achieves state-of-the-art rendering quality and efficiency on monocular dynamic scene reconstruction using deformable 3D Gaussians. Implicit deformable rep…
Efficient Graphics Representation with Differentiable Indirection
Sayantan Datta, Carl Marshall, Derek Nowrouzezahrai +2
We introduce differentiable indirection -- a novel learned primitive that employs differentiable multi-scale lookup tables as an effective substitute for traditional compute and da…