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Related papers: ZeroScene: A Zero-Shot Framework for 3D Scene Gene…

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Recent advances in 3D foundation models have led to growing interest in reconstructing humans and their surrounding environments. However, most existing approaches focus on monocular inputs, and extending them to multi-view settings…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Sangmin Kim , Minhyuk Hwang , Geonho Cha , Dongyoon Wee , Jaesik Park

Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from significant view changes and scene scale. Previous efforts mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Marc Pollefeys , Martin R. Oswald

3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further increased interest in this area. Existing methods broadly follow…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haozhi Zhu , Miaomiao Zhao , Dingyao Liu , Runze Tian , Yan Zhang , Jie Guo , Fenggen Yu

Zero-shot neural scene segmentation, which reconstructs 3D neural segmentation field without manual annotations, serves as an effective way for scene understanding. However, existing models, especially the efficient 3D Gaussian-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Bin Dou , Tianyu Zhang , Zhaohui Wang , Yongjia Ma , Zejian Yuan

Creating machines capable of understanding the world in 3D is essential in assisting designers that build and edit 3D environments and robots navigating and interacting within a three-dimensional space. Inspired by advances in language and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Aadarsh Sahoo , Vansh Tibrewal , Georgia Gkioxari

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

Recent CLIP-guided 3D optimization methods, such as DreamFields and PureCLIPNeRF, have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch training and random initialization without prior knowledge, these…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Jiale Xu , Xintao Wang , Weihao Cheng , Yan-Pei Cao , Ying Shan , Xiaohu Qie , Shenghua Gao

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

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

In the field of digital content creation, generating high-quality 3D characters from single images is challenging, especially given the complexities of various body poses and the issues of self-occlusion and pose ambiguity. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Hao-Yang Peng , Jia-Peng Zhang , Meng-Hao Guo , Yan-Pei Cao , Shi-Min Hu

3D point cloud segmentation remains challenging for structureless and textureless regions. We present a new unified point-based framework for 3D point cloud segmentation that effectively optimizes pixel-level features, geometrical…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Hung-Yueh Chiang , Yen-Liang Lin , Yueh-Cheng Liu , Winston H. Hsu

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

Current successful methods of 3D scene perception rely on the large-scale annotated point cloud, which is tedious and expensive to acquire. In this paper, we propose Model2Scene, a novel paradigm that learns free 3D scene representation…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Runnan Chen , Xinge Zhu , Nenglun Chen , Dawei Wang , Wei Li , Yuexin Ma , Ruigang Yang , Tongliang Liu , Wenping Wang

Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jinghao Zhou , Tomas Jakab , Philip Torr , Christian Rupprecht

This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spatial cue within the perturbed distribution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zipeng Qi , Guoxi Huang , Chenyang Liu , Fei Ye

Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates our investigation of how these pre-trained models can be…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Aditya Sanghi , Pradeep Kumar Jayaraman , Arianna Rampini , Joseph Lambourne , Hooman Shayani , Evan Atherton , Saeid Asgari Taghanaki

3D point cloud generation by the deep neural network from a single image has been attracting more and more researchers' attention. However, recently-proposed methods require the objects be captured with relatively clean backgrounds, fixed…

Computer Vision and Pattern Recognition · Computer Science 2018-09-11 Yan Xia , Yang Zhang , Dingfu Zhou , Xinyu Huang , Cheng Wang , Ruigang Yang

Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Shuai Yang , Yifan Zhou , Ziwei Liu , Chen Change Loy

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

Generating interactive and dynamic 4D scenes from a single static image remains a core challenge. Most existing generate-then-reconstruct and reconstruct-then-generate methods decouple geometry from motion, causing spatiotemporal…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yanran Zhang , Ziyi Wang , Wenzhao Zheng , Zheng Zhu , Jie Zhou , Jiwen Lu