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20242026
most citedMeschers: Geometry Processing of Impossible Objects

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.GR20261 cited

Meschers: Geometry Processing of Impossible Objects

Ana Dodik, Isabella Yu, Kartik Chandra +4

Impossible objects, geometric constructions that humans can perceive but that cannot exist in real life, have been a topic of intrigue in visual arts, perception, and graphics, yet…

cs.LG2026

Mirror Bridges Between Probability Measures

Leticia Mattos Da Silva, Silvia Sellán, Francisco Vargas +1

Resampling from a target measure whose density is unknown is a fundamental problem in mathematical statistics and machine learning. A setting that dominates the machine learning li…

cs.CV2025

Locality in Image Diffusion Models Emerges from Data Statistics

Artem Lukoianov, Chenyang Yuan, Justin Solomon +1

Recent work has shown that the generalization ability of image diffusion models arises from the locality properties of the trained neural network. In particular, when denoising a p…

cs.GR2025

Robust Biharmonic Skinning Using Geometric Fields

Ana Dodik, Vincent Sitzmann, Justin Solomon +1

Bounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to define feature descriptors for geometry…

cs.CV2024

Score Distillation via Reparametrized DDIM

Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan Greenewald +4

While 2D diffusion models generate realistic, high-detail images, 3D shape generation methods like Score Distillation Sampling (SDS) built on these 2D diffusion models produce cart…