arXiv:2606. 28656v1 Announce Type: cross Abstract: Deformable 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for rendering dynamic scenes in a wide range of 3D applications.
By Ruitao Chen, Mozhang Guo, Jinge Li
arXiv:2609.14521v1 Announce Type: new
Abstract: Recovering editable 3D parametric curves from 2D images is a fundamental challenge in computer graphics, bridging pixel-based perception and vector-bas...
By Zhirui Gao, Renjiao Yi, Yunfan Ye, Ruizhen Hu, Chenyang Zhu, Wei Chen, Kai Xu
arXiv:2603. 05607v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit design histories or boundary representation (BRep) labels.
By Mohammad Sadil Khan, Muhammad Usama, Rolandos Alexandros Potamias, Didier Stricker, Muhammad Zeshan Afzal, Jiankang Deng, Ismail Elezi
arXiv:2609.18034v1 Announce Type: new
Abstract: Novel view synthesis from unposed multi-view images remains challenging, as the model must jointly learn scene representations and camera parameters wi...
By Wenyu Li, Sidun Liu, Peng Qiao, Yong Dou, Tongrui Hu
arXiv:2511.21265v2 Announce Type: replace
Abstract: Learning-based image matching critically depends on large-scale, diverse, and geometrically accurate training data. 3D Gaussian Splatting (3DGS) en...
By Juncheng Chen, Chao Xu, Yanjun Cao
PointGT is a point-based 3D representation that allows simultaneous editing of both object geometry and appearance. Unlike volumetric 3D representations, which are hard to edit, PointGT combines a geometry-friendly point structure with a learned UV mapping for high-resolution texture editing. The method demonstrates fine-grained edits to geometry and texture while maintaining high rendering quality.
PointGT is a point-based 3D representation that allows simultaneous editing of both geometry and texture. It combines a point-based structure, which is well-suited for geometry deformations, with a learned UV mapping technique that supports high-resolution texture editing. The method demonstrates fine-grained editing capabilities while maintaining high rendering quality.
By Yanshu Zhang, George Shramko, Pratul P. Srinivasan, Ke Li
arXiv:2607. 00885v1 Announce Type: cross Abstract: Recent advances in neural rendering have established 3D Gaussian Splatting (3DGS) as a highly efficient representation for novel view synthesis, enabling fast training and real-time rendering with strong fidelity.
By Kangmin Seo, Sangeek Hyun, MinKyu Lee, Jae-Pil Heo
Mesh subdivision is a fundamental operation for converting coarse, editable meshes into high-resolution surfaces, with broad applications in digital asset creation. Classical rule-based schemes rely on fixed local refinement rules and often produce over-smoothed surfaces.
arXiv:2609.18473v1 Announce Type: new
Abstract: We present CADSplat, a framework that reconstructs photorealistic, geometrically accurate digital twins from sparse ($<15$ views), wide-baseline posed...
By Kristof Overdulve, Lode Jorissen, Nick Michiels
arXiv:2606. 05142v1 Announce Type: cross Abstract: Recent developments in multi-view image editing with generative models have brought us a step closer toward general 3D content generation and customization.
By Josef Bengtson, Yaroslava Lochman, Fredrik Kahl
The paper introduces a generalizable deformation learning framework that reconstructs 3D objects by deforming a category-level shape template to match a monocular observation. It employs a geometry-guided feature modeling mechanism to enrich foundation features with template topology, creating a geometry-aware representation that is explicitly correlated with the target observation for precise deformation. A view-adaptive feature aggregation module further bridges the gap between the fixed template and arbitrary target views by leveraging multi-view template features and camera poses, ensuring robust feature alignment across diverse viewpoints.
By Yiyao Ma, Kai Chen, Zhongxiang Zhou, Zhuheng Song, Dongsheng Xie, Zelong Tan, Rong Xiong, Qi Dou