English
Related papers

Related papers: StdGEN++: A Comprehensive System for Semantic-Deco…

200 papers

This paper presents a novel decoder-based approach for generating manufacturable 3D structures optimized for additive manufacturing. We introduce a deep learning framework that decodes latent representations into geometrically valid,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Abhishek Kumar

The availability of rich 3D datasets corresponding to the geometrical complexity of the built environments is considered an ongoing challenge for 3D deep learning methodologies. To address this challenge, we introduce GenScan, a generative…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Mohammad Keshavarzi , Oladapo Afolabi , Luisa Caldas , Allen Y. Yang , Avideh Zakhor

We introduce DreamCraft3D++, an extension of DreamCraft3D that enables efficient high-quality generation of complex 3D assets. DreamCraft3D++ inherits the multi-stage generation process of DreamCraft3D, but replaces the time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Jingxiang Sun , Cheng Peng , Ruizhi Shao , Yuan-Chen Guo , Xiaochen Zhao , Yangguang Li , Yanpei Cao , Bo Zhang , Yebin Liu

Face sketch synthesis has made significant progress with the development of deep neural networks in these years. The delicate depiction of sketch portraits facilitates a wide range of applications like digital entertainment and law…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Xingqun Qi , Muyi Sun , Weining Wang , Xiaoxiao Dong , Qi Li , Caifeng Shan

With the growing demand for high-fidelity 3D models from 2D images, existing methods still face significant challenges in accurately reproducing fine-grained geometric details due to limitations in domain gaps and inherent ambiguities in…

Graphics · Computer Science 2025-04-01 Chongjie Ye , Yushuang Wu , Ziteng Lu , Jiahao Chang , Xiaoyang Guo , Jiaqing Zhou , Hao Zhao , Xiaoguang Han

Text-to-3D generation has recently seen significant progress. To enhance its practicality in real-world applications, it is crucial to generate multiple independent objects with interactions, similar to layer-compositing in 2D image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Zizheng Yan , Jiapeng Zhou , Fanpeng Meng , Yushuang Wu , Lingteng Qiu , Zisheng Ye , Shuguang Cui , Guanying Chen , Xiaoguang Han

Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretrained state-of-the-art generation models, guided by 2D layout…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yishen Ji , Ziyue Zhu , Zhenxin Zhu , Kaixin Xiong , Ming Lu , Zhiqi Li , Lijun Zhou , Haiyang Sun , Bing Wang , Tong Lu

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

We introduce a new generative approach for synthesizing 3D geometry and images from single-view collections. Most existing approaches predict volumetric density to render multi-view consistent images. By employing volumetric rendering using…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Salvatore Esposito , Qingshan Xu , Kacper Kania , Charlie Hewitt , Octave Mariotti , Lohit Petikam , Julien Valentin , Arno Onken , Oisin Mac Aodha

Generative models have gained significant attention in novel view synthesis (NVS) by alleviating the reliance on dense multi-view captures. However, existing methods typically fall into a conventional paradigm, where generative models first…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Weiliang Chen , Jiayi Bi , Yuanhui Huang , Wenzhao Zheng , Yueqi Duan

3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isolation without…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Ruikai Cui , Weizhe Liu , Weixuan Sun , Senbo Wang , Taizhang Shang , Yang Li , Xibin Song , Han Yan , Zhennan Wu , Shenzhou Chen , Hongdong Li , Pan Ji

In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various difficulties such as scalability, cost efficiency and photorealism. To avoid…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Chahat Deep Singh , Riya Kumari , Cornelia Fermüller , Nitin J. Sanket , Yiannis Aloimonos

The generation of 3D clothed humans has attracted increasing attention in recent years. However, existing work cannot generate layered high-quality 3D humans with consistent body structures. As a result, these methods are unable to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yi Wang , Jian Ma , Ruizhi Shao , Qiao Feng , Yu-Kun Lai , Yebin Liu , Kun Li

In this work, we present a novel framework built to simplify 3D asset generation for amateur users. To enable interactive generation, our method supports a variety of input modalities that can be easily provided by a human, including…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Yen-Chi Cheng , Hsin-Ying Lee , Sergey Tulyakov , Alexander Schwing , Liangyan Gui

Automatic text-to-3D generation that combines Score Distillation Sampling (SDS) with the optimization of volume rendering has achieved remarkable progress in synthesizing realistic 3D objects. Yet most existing text-to-3D methods by SDS and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Zilong Chen , Feng Wang , Yikai Wang , Huaping Liu

Existing generative models for 3D shapes can synthesize high-fidelity and visually plausible shapes. For certain classes of shapes that have undergone an engineering design process, the realism of the shape is tightly coupled with the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yingxuan You , Chen Zhao , Hantao Zhang , Ming Xu , Pascal Fua

Generating coherent and useful image/video scenes from a free-form textual description is technically a very difficult problem to handle. Textual description of the same scene can vary greatly from person to person, or sometimes even for…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Faria Huq , Nafees Ahmed , Anindya Iqbal

Animatable 3D assets, defined as geometry equipped with an articulated skeleton and skinning weights, are fundamental to interactive graphics, embodied agents, and animation production. While recent 3D generative models can synthesize…

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

3D Gaussian Splatting (3DGS) has recently redefined the paradigm of 3D reconstruction, striking an unprecedented balance between visual fidelity and computational efficiency. As its adoption proliferates, safeguarding the copyright of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Yijia Guo , Wenkai Huang , Tong Hu , Gaolei Li , Yang Li , Yuxin Hong , Liwen Hu , Xitong Ling , Jianhua Li , Shengbo Chen , Tiejun Huang , Lei Ma
‹ Prev 1 3 4 5 6 7 10 Next ›