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Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

Although recent 3D-native generators have made great progress in synthesizing reliable geometry, they still fall short in achieving realistic appearances. A key obstacle lies in the lack of diverse and high-quality real-world 3D assets with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xinyue Liang , Zhinyuan Ma , Lingchen Sun , Yanjun Guo , Lei Zhang

Generating artistic and coherent 3D scene layouts is crucial in digital content creation. Traditional optimization-based methods are often constrained by cumbersome manual rules, while deep generative models face challenges in producing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Xiaoming Zhu , Xu Huang , Qinghongbing Xie , Zhi Deng , Junsheng Yu , Yirui Guan , Zhongyuan Liu , Lin Zhu , Qijun Zhao , Ligang Liu , Long Zeng

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H

With the widespread usage of VR devices and contents, demands for 3D scene generation techniques become more popular. Existing 3D scene generation models, however, limit the target scene to specific domain, primarily due to their training…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jaeyoung Chung , Suyoung Lee , Hyeongjin Nam , Jaerin Lee , Kyoung Mu Lee

In recent years, 3D models have been utilized in many applications, such as auto-driver, 3D reconstruction, VR, and AR. However, the scarcity of 3D model data does not meet its practical demands. Thus, generating high-quality 3D models…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Weizhi Nie , Ruidong Chen , Weijie Wang , Bruno Lepri , Nicu Sebe

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng

We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100$\times$ faster than previous works while possessing superior rendering quality. Our approach shifts from the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyang Li , Tengfei Wang , Zixiao Gu , Shengchuan Zhang , Chunchao Guo , Liujuan Cao

Although text-to-image diffusion models have made significant strides in generating images from text, they are sometimes more inclined to generate images like the data on which the model was trained rather than the provided text. This…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Mohammadreza Armandpour , Ali Sadeghian , Huangjie Zheng , Amir Sadeghian , Mingyuan Zhou

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

Recent advancements in video generation have primarily leveraged diffusion models for short-duration content. However, these approaches often fall short in modeling complex narratives and maintaining character consistency over extended…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Canyu Zhao , Mingyu Liu , Wen Wang , Weihua Chen , Fan Wang , Hao Chen , Bo Zhang , Chunhua Shen

We present a new method for generating realistic and view-consistent images with fine geometry from 2D image collections. Our method proposes a hybrid explicit-implicit representation called \textbf{OrthoPlanes}, which encodes fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2023-09-28 Honglin He , Zhuoqian Yang , Shikai Li , Bo Dai , Wayne Wu

Text-guided 3D editing aims to precisely edit semantically relevant local 3D regions, which has significant potential for various practical applications ranging from 3D games to film production. Existing methods typically follow a…

Graphics · Computer Science 2025-06-04 Yang Zheng , Mengqi Huang , Nan Chen , Zhendong Mao

We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ahmet Burak Yildirim , Mustafa Utku Aydogdu , Duygu Ceylan , Aysegul Dundar

Traditional 3D garment creation is labor-intensive, involving sketching, modeling, UV mapping, and texturing, which are time-consuming and costly. Recent advances in diffusion-based generative models have enabled new possibilities for 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Boqian Li , Xuan Li , Ying Jiang , Tianyi Xie , Feng Gao , Huamin Wang , Yin Yang , Chenfanfu Jiang

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

In the realm of high-resolution (HR), fine-grained image segmentation, the primary challenge is balancing broad contextual awareness with the precision required for detailed object delineation, capturing intricate details and the finest…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Qian Yu , Peng-Tao Jiang , Hao Zhang , Jinwei Chen , Bo Li , Lihe Zhang , Huchuan Lu

We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion model can achieve the generalizability of 2D diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Yichun Shi , Peng Wang , Jianglong Ye , Mai Long , Kejie Li , Xiao Yang

With the rapid advancements in diffusion models and 3D generation techniques, dynamic 3D content generation has become a crucial research area. However, achieving high-fidelity 4D (dynamic 3D) generation with strong spatial-temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Jinwei Li , Huan-ang Gao , Wenyi Li , Haohan Chi , Chenyu Liu , Chenxi Du , Yiqian Liu , Mingju Gao , Guiyu Zhang , Zongzheng Zhang , Li Yi , Yao Yao , Jingwei Zhao , Hongyang Li , Yikai Wang , Hao Zhao
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