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Utilizing pre-trained 2D large-scale generative models, recent works are capable of generating high-quality novel views from a single in-the-wild image. However, due to the lack of information from multiple views, these works encounter…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Yunhan Yang , Yukun Huang , Xiaoyang Wu , Yuan-Chen Guo , Song-Hai Zhang , Hengshuang Zhao , Tong He , Xihui Liu

Deep generative models of 3D shapes have received a great deal of research interest. Yet, almost all of them generate discrete shape representations, such as voxels, point clouds, and polygon meshes. We present the first 3D generative model…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Rundi Wu , Chang Xiao , Changxi Zheng

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models. We formulate the 3D-aware image generation task as multiview 2D image set generation, and further to a sequential…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Jianfeng Xiang , Jiaolong Yang , Binbin Huang , Xin Tong

Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Frank Zhang , Yibo Zhang , Quan Zheng , Rui Ma , Wei Hua , Hujun Bao , Weiwei Xu , Changqing Zou

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

It is inherently ambiguous to lift 2D results from pre-trained diffusion models to a 3D world for text-to-3D generation. 2D diffusion models solely learn view-agnostic priors and thus lack 3D knowledge during the lifting, leading to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Weiyu Li , Rui Chen , Xuelin Chen , Ping Tan

Existing single image-to-3D creation methods typically involve a two-stage process, first generating multi-view images, and then using these images for 3D reconstruction. However, training these two stages separately leads to significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Hao Wen , Zehuan Huang , Yaohui Wang , Xinyuan Chen , Lu Sheng

Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D biases, resulting in compromised geometric consistency. To…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Hansheng Chen , Bokui Shen , Yulin Liu , Ruoxi Shi , Linqi Zhou , Connor Z. Lin , Jiayuan Gu , Hao Su , Gordon Wetzstein , Leonidas Guibas

Detailed and photorealistic 3D human modeling is essential for various applications and has seen tremendous progress. However, full-body reconstruction from a monocular RGB image remains challenging due to the ill-posed nature of the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Peng Li , Wangguandong Zheng , Yuan Liu , Tao Yu , Yangguang Li , Xingqun Qi , Xiaowei Chi , Siyu Xia , Yan-Pei Cao , Wei Xue , Wenhan Luo , Yike Guo

We present an approach to generate a 360-degree view of a person with a consistent, high-resolution appearance from a single input image. NeRF and its variants typically require videos or images from different viewpoints. Most existing…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Badour AlBahar , Shunsuke Saito , Hung-Yu Tseng , Changil Kim , Johannes Kopf , Jia-Bin Huang

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

The boundary representation (B-Rep) is the standard data structure used in Computer-Aided Design (CAD) for defining solid models. Despite recent progress, directly generating B-Reps end-to-end with precise geometry and watertight topology…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Xiang Xu , Pradeep Kumar Jayaraman , Joseph G. Lambourne , Yilin Liu , Durvesh Malpure , Pete Meltzer

Generating multiview images from a single view facilitates the rapid generation of a 3D mesh conditioned on a single image. Recent methods that introduce 3D global representation into diffusion models have shown the potential to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Zehuan Huang , Hao Wen , Junting Dong , Yaohui Wang , Yangguang Li , Xinyuan Chen , Yan-Pei Cao , Ding Liang , Yu Qiao , Bo Dai , Lu Sheng

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Text-driven image generation using diffusion models has recently gained significant attention. To enable more flexible image manipulation and editing, recent research has expanded from single image generation to transparent layer generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Junjia Huang , Pengxiang Yan , Jinhang Cai , Jiyang Liu , Zhao Wang , Yitong Wang , Xinglong Wu , Guanbin Li

With the advancement of generative AI, research on its application to 3D model generation has gained traction, particularly in automating the creation of Computer-Aided Design (CAD) files from images. GenCAD is a notable model in this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Chikaha Tsuji , Enrique Flores Medina , Harshit Gupta , Md Ferdous Alam

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

2D-to-3D reconstruction is an ill-posed problem, yet humans are good at solving this problem due to their prior knowledge of the 3D world developed over years. Driven by this observation, we propose NeRDi, a single-view NeRF synthesis…

Computer Vision and Pattern Recognition · Computer Science 2022-12-08 Congyue Deng , Chiyu "Max'' Jiang , Charles R. Qi , Xinchen Yan , Yin Zhou , Leonidas Guibas , Dragomir Anguelov

Creating CAD digital twins from the physical world is crucial for manufacturing, design, and simulation. However, current methods typically rely on costly 3D scanning with labor-intensive post-processing. To provide a user-friendly design…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Cheng Chen , Jiacheng Wei , Tianrun Chen , Chi Zhang , Xiaofeng Yang , Shangzhan Zhang , Bingchen Yang , Chuan-Sheng Foo , Guosheng Lin , Qixing Huang , Fayao Liu
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