activity
20202026
most citedMultiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

145 citations · 156 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions

Or Perel, Hassan Abu Alhaija, Zian Wang +4

We introduce TRON, a rendering framework that combines 3D Gaussian ray tracing with neural rendering to enable realistic and controllable rendering of real-world 3D scenes under no…

cs.LG2026

Variance Reduction for Expectations with Diffusion Teachers

Jesse Bettencourt, Xindi Wu, Matan Atzmon +2

Pretrained diffusion models serve as frozen teachers feeding downstream pipelines such as text-to-3D, single-step distillation, and data attribution. The teacher gradients these pi…

cs.CV2024

ReMatching Dynamic Reconstruction Flow

Sara Oblak, Despoina Paschalidou, Sanja Fidler +1

Reconstructing a dynamic scene from image inputs is a fundamental computer vision task with many downstream applications. Despite recent advancements, existing approaches still str…

cs.CV2024★ 11 cited

SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes

Tianchang Shen, Zhaoshuo Li, Marc Law +5

Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or…

cs.LG2024

Approximately Piecewise E(3) Equivariant Point Networks

Matan Atzmon, Jiahui Huang, Francis Williams +1

Integrating a notion of symmetry into point cloud neural networks is a provably effective way to improve their generalization capability. Of particular interest are equivari…

cs.CV2023

Neural Kernel Surface Reconstruction

Jiahui Huang, Zan Gojcic, Matan Atzmon +3

We present a novel method for reconstructing a 3D implicit surface from a large-scale, sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural Kernel…

cs.CV2020★ 145 cited

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

Lior Yariv, Yoni Kasten, Dror Moran +4

In this work we address the challenging problem of multiview 3D surface reconstruction. We introduce a neural network architecture that simultaneously learns the unknown geometry,…