18 citations · 28 across the 13 of their papers we have counts for
13 papers
MegaSynth: Scaling Up 3D Scene Reconstruction with Synthesized Data
Hanwen Jiang, Zexiang Xu, Desai Xie +11
We propose scaling up 3D scene reconstruction by training with synthesized data. At the core of our work is MegaSynth, a procedurally generated 3D dataset comprising 700K scenes -…
TutteNet: Injective 3D Deformations by Composition of 2D Mesh Deformations
Bo Sun, Thibault Groueix, Chen Song +2
This work proposes a novel representation of injective deformations of 3D space, which overcomes existing limitations of injective methods: inaccuracy, lack of robustness, and inco…
4DRecons: 4D Neural Implicit Deformable Objects Reconstruction from a single RGB-D Camera with Geometrical and Topological Regularizations
Xiaoyan Cong, Haitao Yang, Liyan Chen +4
This paper presents a novel approach 4DRecons that takes a single camera RGB-D sequence of a dynamic subject as input and outputs a complete textured deforming 3D model over time.…
Real3D: Scaling Up Large Reconstruction Models with Real-World Images
Hanwen Jiang, Qixing Huang, Georgios Pavlakos
The default strategy for training single-view Large Reconstruction Models (LRMs) follows the fully supervised route using large-scale datasets of synthetic 3D assets or multi-view…
CoFie: Learning Compact Neural Surface Representations with Coordinate Fields
Hanwen Jiang, Haitao Yang, Georgios Pavlakos +1
This paper introduces CoFie, a novel local geometry-aware neural surface representation. CoFie is motivated by the theoretical analysis of local SDFs with quadratic approximation.…
Freditor: High-Fidelity and Transferable NeRF Editing by Frequency Decomposition
Yisheng He, Weihao Yuan, Siyu Zhu +3
This paper enables high-fidelity, transferable NeRF editing by frequency decomposition. Recent NeRF editing pipelines lift 2D stylization results to 3D scenes while suffering from…