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Open-world 3D generation has recently attracted considerable attention. While many single-image-to-3D methods have yielded visually appealing outcomes, they often lack sufficient controllability and tend to produce hallucinated regions that…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Chao Xu , Ang Li , Linghao Chen , Yulin Liu , Ruoxi Shi , Hao Su , Minghua Liu

Interactive 3D generation is gaining momentum and capturing extensive attention for its potential to create immersive virtual experiences. However, a critical challenge in current 3D generation technologies lies in achieving real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Chaojun Ni , Xiaofeng Wang , Zheng Zhu , Weijie Wang , Haoyun Li , Guosheng Zhao , Jie Li , Wenkang Qin , Guan Huang , Wenjun Mei

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

We present a latent diffusion model over 3D scenes, that can be trained using only 2D image data. To achieve this, we first design an autoencoder that maps multi-view images to 3D Gaussian splats, and simultaneously builds a compressed…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Paul Henderson , Melonie de Almeida , Daniela Ivanova , Titas Anciukevičius

Tuning-free diffusion-based models have demonstrated significant potential in the realm of image personalization and customization. However, despite this notable progress, current models continue to grapple with several complex challenges…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Haofan Wang , Matteo Spinelli , Qixun Wang , Xu Bai , Zekui Qin , Anthony Chen

Large Reconstruction Models have made significant strides in the realm of automated 3D content generation from single or multiple input images. Despite their success, these models often produce 3D meshes with geometric inaccuracies,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Ruikai Cui , Xibin Song , Weixuan Sun , Senbo Wang , Weizhe Liu , Shenzhou Chen , Taizhang Shang , Yang Li , Nick Barnes , Hongdong Li , Pan Ji

Rendering is the process of generating 2D images from 3D assets, simulated in a virtual environment, typically with a graphics pipeline. By inverting such renderer, one can think of a learning approach to predict a 3D shape from an input…

Computer Vision and Pattern Recognition · Computer Science 2019-01-24 Shichen Liu , Weikai Chen , Tianye Li , Hao Li

The emerging trend of AR/VR places great demands on 3D content. However, most existing software requires expertise and is difficult for novice users to use. In this paper, we aim to create sketch-based modeling tools for user-friendly 3D…

Human-Computer Interaction · Computer Science 2023-10-30 Tianrun Chen , Chaotao Ding , Lanyun Zhu , Ying Zang , Yiyi Liao , Zejian Li , Lingyun Sun

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

We present StdGEN, an innovative pipeline for generating semantically decomposed high-quality 3D characters from single images, enabling broad applications in virtual reality, gaming, and filmmaking, etc. Unlike previous methods which…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Yuze He , Yanning Zhou , Wang Zhao , Zhongkai Wu , Kaiwen Xiao , Wei Yang , Yong-Jin Liu , Xiao Han

We propose Flash3D, a method for scene reconstruction and novel view synthesis from a single image which is both very generalisable and efficient. For generalisability, we start from a "foundation" model for monocular depth estimation and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Stanislaw Szymanowicz , Eldar Insafutdinov , Chuanxia Zheng , Dylan Campbell , João F. Henriques , Christian Rupprecht , Andrea Vedaldi

A key challenge in fine-grained 3D-based interactive editing is the absence of an efficient representation that balances diverse modifications with high-quality view synthesis under a given memory constraint. While 3D meshes provide…

Inspired by generative paradigms in image and video, 3D shape generation has made notable progress, enabling the rapid synthesis of high-fidelity 3D assets from a single image. However, current methods still face challenges, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yangguang Li , Xianglong He , Zi-Xin Zou , Zexiang Liu , Wanli Ouyang , Ding Liang , Yan-Pei Cao

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

We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model. Given the noisy multi-view latents, the 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Xinyang Li , Zhangyu Lai , Linning Xu , Jianfei Guo , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

Template generation is a critical step in groupwise image registration, which involves aligning a group of subjects into a common space. While existing methods can generate high-quality template images, they often incur substantial time…

Image and Video Processing · Electrical Eng. & Systems 2025-07-17 Ziyi He , Albert C. S. Chung

How can we extract complete geometric models of objects that we encounter in our daily life, without having access to commercial 3D scanners? In this paper we present an automated system for generating geometric models of objects from two…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Floris Erich , Naoya Chiba , Abdullah Mustafa , Ryo Hanai , Noriaki Ando , Yusuke Yoshiyasu , Yukiyasu Domae

The synthesis of high-quality 3D assets from textual or visual inputs has become a central objective in modern generative modeling. Despite the proliferation of 3D generation algorithms, they frequently grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Hwan Heo , Jangyeong Kim , Seongyeong Lee , Jeong A Wi , Junyoung Choi , Sangjun Ahn

We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditional graph-cut based mesh generation. Specifically, we first…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Shuang Song , Zhaopeng Cui , Rongjun Qin

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Xingyi Li , Yizheng Wu , Jun Cen , Juewen Peng , Kewei Wang , Ke Xian , Zhe Wang , Zhiguo Cao , Guosheng Lin
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