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20242026
most citedGEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis

2 citations · 2 across the 7 of their papers we have counts for

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cs.CV2026

LumiTokens: 3D Relighting via Token-Space Lighting Transformation

Yiwen Chen, Matheus Gadelha, Huaizu Jiang

Existing 3D relighting methods operate through either explicit material decomposition, diffusion-based view-space generation, or a combination of both, requiring full recomputation…

cs.CV2026

ViPS: Video-informed Pose Spaces for Auto-Rigged Meshes

Honglin Chen, Karran Pandey, Rundi Wu +6

Kinematic rigs provide a structured interface for articulating 3D meshes but lack any associated pose space, i.e., an explicit representation of the plausible manifold of joint con…

cs.CV2026

Material Magic Wand: Material-Aware Grouping of 3D Parts in Untextured Meshes

Umangi Jain, Vladimir Kim, Matheus Gadelha +2

We introduce the problem of material-aware part grouping in untextured meshes. Many real-world shapes, such as scales of pinecones or windows of buildings, contain repeated structu…

cs.CV2024

Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects

Amir Barda, Matheus Gadelha, Vladimir G. Kim +3

We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in approximately 3 seconds, without the need for running an SDS type of optim…

cs.CV2024

Text-guided Controllable Mesh Refinement for Interactive 3D Modeling

Yun-Chun Chen, Selena Ling, Zhiqin Chen +3

We propose a novel technique for adding geometric details to an input coarse 3D mesh guided by a text prompt. Our method is composed of three stages. First, we generate a single-vi…

cs.CV2024★ 2 cited

GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis

Dmitry Petrov, Pradyumn Goyal, Vikas Thamizharasan +5

We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on b…