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Understanding three-dimensional (3D) geometries from two-dimensional (2D) images without any labeled information is promising for understanding the real world without incurring annotation cost. We herein propose a novel generative model,…

Computer Vision and Pattern Recognition · Computer Science 2020-05-26 Atsuhiro Noguchi , Tatsuya Harada

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

A classical problem in computer vision is to infer a 3D scene representation from few images that can be used to render novel views at interactive rates. Previous work focuses on reconstructing pre-defined 3D representations, e.g. textured…

3D scene generation has long been dominated by 2D multi-view or video diffusion models. This is due not only to the lack of scene-level 3D latent representation, but also to the fact that most scene-level 3D visual data exists in the form…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dongxu Wei , Qi Xu , Zhiqi Li , Hangning Zhou , Cong Qiu , Hailong Qin , Mu Yang , Zhaopeng Cui , Peidong Liu

Indoor scene texture synthesis has garnered significant interest due to its important potential applications in virtual reality, digital media and creative arts. Existing diffusion-model-based researches either rely on per-view inpainting…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Zhipeng Huang , Wangbo Yu , Xinhua Cheng , ChengShu Zhao , Yunyang Ge , Mingyi Guo , Li Yuan , Yonghong Tian

Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem. In this paper, we propose an efficient method to reconstruct the scene's 3D geometry and reflectance from…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Rui Li , Guangmin Zang , Miao Qi , Wolfgang Heidrich

Despite recent advances in leveraging generative prior from pre-trained diffusion models for 3D scene reconstruction, existing methods still face two critical limitations. First, due to the lack of reliable geometric supervision, they…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Junfeng Ni , Yixin Chen , Zhifei Yang , Yu Liu , Ruijie Lu , Song-Chun Zhu , Siyuan Huang

Image inpainting is a widely used technique in computer vision for reconstructing missing or damaged pixels in images. Recent advancements with Generative Adversarial Networks (GANs) have demonstrated superior performance over traditional…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Nafiz Al Asad , Md. Appel Mahmud Pranto , Shbiruzzaman Shiam , Musaddeq Mahmud Akand , Mohammad Abu Yousuf , Khondokar Fida Hasan , Mohammad Ali Moni

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

Latent diffusion models have proven to be state-of-the-art in the creation and manipulation of visual outputs. However, as far as we know, the generation of depth maps jointly with RGB is still limited. We introduce LDM3D-VR, a suite of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Gabriela Ben Melech Stan , Diana Wofk , Estelle Aflalo , Shao-Yen Tseng , Zhipeng Cai , Michael Paulitsch , Vasudev Lal

We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single images from the Internet. Prior works on 3D-aware image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangzan Zhang , Sida Peng , Tianrun Chen , Linzhan Mou , Haotong Lin , Kaicheng Yu , Yiyi Liao , Xiaowei Zhou

The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple single-view image. However, due to the partial priors provided by single-view input, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Tianyi Gong , Boyan Li , Yifei Zhong , Fangxin Wang

We propose a novel superpixel-based multi-view convolutional neural network for semantic image segmentation. The proposed network produces a high quality segmentation of a single image by leveraging information from additional views of the…

Computer Vision and Pattern Recognition · Computer Science 2017-04-27 Yang He , Wei-Chen Chiu , Margret Keuper , Mario Fritz

Over the last few years, deep learning techniques have yielded significant improvements in image inpainting. However, many of these techniques fail to reconstruct reasonable structures as they are commonly over-smoothed and/or blurry. This…

Computer Vision and Pattern Recognition · Computer Science 2019-01-14 Kamyar Nazeri , Eric Ng , Tony Joseph , Faisal Z. Qureshi , Mehran Ebrahimi

Detailed 3D reconstruction is an important challenge with application to robotics, augmented and virtual reality, which has seen impressive progress throughout the past years. Advancements were driven by the availability of depth cameras…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Andrea Nicastro , Ronald Clark , Stefan Leutenegger

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

In this paper we propose a new problem scenario in image processing, wide-range image blending, which aims to smoothly merge two different input photos into a panorama by generating novel image content for the intermediate region between…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Chia-Ni Lu , Ya-Chu Chang , Wei-Chen Chiu

Large-scale text-guided image diffusion models have shown astonishing results in text-to-image (T2I) generation. However, applying these models to synthesize textures for 3D geometries remains challenging due to the domain gap between 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Jiawei Lu , Yingpeng Zhang , Zengjun Zhao , He Wang , Kun Zhou , Tianjia Shao

Recent advances in 3D scene representations have enabled high-fidelity novel view synthesis, yet adapting to discrete scene changes and constructing interactive 3D environments remain open challenges in vision and robotics. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Wenhao Hu , Haonan Zhou , Zesheng Li , Liu Liu , Jiacheng Dong , Zhizhong Su , Gaoang Wang