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Realistic and efficient 3D garment generation remains a longstanding challenge in computer vision and digital fashion. Existing methods typically rely on large vision- language models to produce serialized representations of 2D sewing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Phuc Pham , Uy Dieu Tran , Binh-Son Hua , Phong Nguyen

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai

Open-world 3D reconstruction models have recently garnered significant attention. However, without sufficient 3D inductive bias, existing methods typically entail expensive training costs and struggle to extract high-quality 3D meshes. In…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Minghua Liu , Chong Zeng , Xinyue Wei , Ruoxi Shi , Linghao Chen , Chao Xu , Mengqi Zhang , Zhaoning Wang , Xiaoshuai Zhang , Isabella Liu , Hongzhi Wu , Hao Su

Mesh seams play a pivotal role in partitioning 3D surfaces for UV parametrization and texture mapping. Poorly placed seams often result in severe UV distortion or excessive fragmentation, thereby hindering texture synthesis and disrupting…

Graphics · Computer Science 2025-09-29 Duoteng Xu , Yuguang Chen , Jing Li , Xinhai Liu , Xueqi Ma , Zhuo Chen , Dongyu Zhang , Chunchao Guo

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are…

Graphics · Computer Science 2023-04-18 Zhen Liu , Yao Feng , Michael J. Black , Derek Nowrouzezahrai , Liam Paull , Weiyang Liu

Scaling artist-designed meshes to high triangle numbers remains challenging for autoregressive generative models. Existing transformer-based methods suffer from long-sequence bottlenecks and limited quantization resolution, primarily due to…

Graphics · Computer Science 2025-11-17 Rui Xu , Tianyang Xue , Qiujie Dong , Le Wan , Zhe Zhu , Peng Li , Zhiyang Dou , Cheng Lin , Shiqing Xin , Yuan Liu , Wenping Wang , Taku Komura

Designing mechanical mechanisms to trace specific paths is a classic yet notoriously difficult engineering problem, characterized by a vast and complex search space of discrete topologies and continuous parameters. We introduce MechaFormer,…

Machine Learning · Computer Science 2025-08-13 Diana Bolanos , Mohammadmehdi Ataei , Pradeep Kumar Jayaraman

We present TexTailor, a novel method for generating consistent object textures from textual descriptions. Existing text-to-texture synthesis approaches utilize depth-aware diffusion models to progressively generate images and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Suin Lee , Dae-Shik Kim

Numerous methods have been proposed for probabilistic generative modelling of 3D objects. However, none of these is able to produce textured objects, which renders them of limited use for practical tasks. In this work, we present the first…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Paul Henderson , Vagia Tsiminaki , Christoph H. Lampert

Meshes serve as a primary representation for 3D assets. Autoregressive mesh generators serialize faces into sequences and train on truncated segments with sliding-window inference to cope with memory limits. However, this mismatch breaks…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Junkai Lin , Hang Long , Huipeng Guo , Jielei Zhang , JiaYi Yang , Tianle Guo , Yang Yang , Jianwen Li , Wenxiao Zhang , Matthias Nießner , Wei Yang

Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control signals, such as contextual descriptions, and rarely supports bold geometric distortions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Changwoon Choi , Hyunsoo Lee , Clément Jambon , Yael Vinker , Young Min Kim

We present SeamlessGAN, a method capable of automatically generating tileable texture maps from a single input exemplar. In contrast to most existing methods, focused solely on solving the synthesis problem, our work tackles both problems,…

Computer Vision and Pattern Recognition · Computer Science 2022-01-14 Carlos Rodriguez-Pardo , Elena Garces

We introduce MeshGPT, a new approach for generating triangle meshes that reflects the compactness typical of artist-created meshes, in contrast to dense triangle meshes extracted by iso-surfacing methods from neural fields. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yawar Siddiqui , Antonio Alliegro , Alexey Artemov , Tatiana Tommasi , Daniele Sirigatti , Vladislav Rosov , Angela Dai , Matthias Nießner

The synthesis of a metasurface exhibiting a specific set of desired scattering properties is a time-consuming and resource-demanding process, which conventionally relies on many cycles of full-wave simulations. It requires an experienced…

Signal Processing · Electrical Eng. & Systems 2021-09-15 Parinaz Naseri , Sean V. Hum

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhaoyang Lyu , Ben Fei , Jinyi Wang , Xudong Xu , Ya Zhang , Weidong Yang , Bo Dai

The fields of SocialVR, performance capture, and virtual try-on are often faced with a need to faithfully reproduce real garments in the virtual world. One critical task is the disentanglement of the intrinsic garment shape from…

Computer Vision and Pattern Recognition · Computer Science 2022-06-29 Maria Korosteleva , Sung-Hee Lee

This paper proposes a fully-automatic, text-guided generative method for producing perfectly-repeating, periodic, tile-able 2D imagery, such as the one seen on floors, mosaics, ceramics, and the work of M.C. Escher. In contrast to square…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Noam Aigerman , Thibault Groueix

Mesh texture synthesis is a key component in the automatic generation of 3D content. Existing learning-based methods have drawbacks -- either by disregarding the shape manifold during texture generation or by requiring a large number of…

Graphics · Computer Science 2024-03-12 Áron Samuel Kovács , Pedro Hermosilla , Renata G. Raidou

Recently there has been a significant effort to automate UV mapping, the process of mapping 3D-dimensional surfaces to the UV space while minimizing distortion and seam length. Although state-of-the-art methods, Autocuts and OptCuts,…

Graphics · Computer Science 2020-12-04 Fatemeh Teimury , Bruno Roy , Juan Sebastián Casallas , David MacDonald , Mark Coates
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