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Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

We present a novel method for 3D surface reconstruction from multiple images where only a part of the object of interest is captured. Our approach builds on two recent developments: surface reconstruction using neural radiance fields for…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Savva Ignatyev , Daniil Selikhanovych , Oleg Voynov , Yiqun Wang , Peter Wonka , Stamatios Lefkimmiatis , Evgeny Burnaev

We present 3DiM, a diffusion model for 3D novel view synthesis, which is able to translate a single input view into consistent and sharp completions across many views. The core component of 3DiM is a pose-conditional image-to-image…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Daniel Watson , William Chan , Ricardo Martin-Brualla , Jonathan Ho , Andrea Tagliasacchi , Mohammad Norouzi

The task of novel view synthesis aims to generate unseen perspectives of an object or scene from a limited set of input images. Nevertheless, synthesizing novel views from a single image still remains a significant challenge in the realm of…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Yifan Jiang , Hao Tang , Jen-Hao Rick Chang , Liangchen Song , Zhangyang Wang , Liangliang Cao

Despite recent advances in Novel View Synthesis (NVS), generating high-fidelity views from single or sparse observations remains a significant challenge. Existing splatting-based approaches often produce distorted geometry due to splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Xiang Zhang , Yang Zhang , Lukas Mehl , Markus Gross , Christopher Schroers

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings consistent with the input and, even in the presence of…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Eric R. Chan , Koki Nagano , Matthew A. Chan , Alexander W. Bergman , Jeong Joon Park , Axel Levy , Miika Aittala , Shalini De Mello , Tero Karras , Gordon Wetzstein

Generating novel views of a natural scene, e.g., every-day scenes both indoors and outdoors, from a single view is an under-explored problem, even though it is an organic extension to the object-centric novel view synthesis. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Wonbong Jang , Jonathan Tremblay , Lourdes Agapito

Researches in novel viewpoint synthesis majorly focus on interpolation from multi-view input images. In this paper, we focus on a more challenging and ill-posed problem that is to synthesize novel viewpoints from one single input image. To…

Computer Vision and Pattern Recognition · Computer Science 2017-11-20 Xiaodong Cun , Feng Xu , Chi-Man Pun , Hao Gao

Novel view synthesis from a single image has been a cornerstone problem for many Virtual Reality applications that provide immersive experiences. However, most existing techniques can only synthesize novel views within a limited range of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Hung-Yu Tseng , Qinbo Li , Changil Kim , Suhib Alsisan , Jia-Bin Huang , Johannes Kopf

Novel view synthesis from a single image requires inferring occluded regions of objects and scenes whilst simultaneously maintaining semantic and physical consistency with the input. Existing approaches condition neural radiance fields…

Computer Vision and Pattern Recognition · Computer Science 2023-02-21 Jiatao Gu , Alex Trevithick , Kai-En Lin , Josh Susskind , Christian Theobalt , Lingjie Liu , Ravi Ramamoorthi

A fundamental bottleneck in Novel View Synthesis (NVS) for autonomous driving is the inherent supervision gap on novel trajectories: models are tasked with synthesizing unseen views during inference, yet lack ground truth images for these…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Hongbo Lu , Liang Yao , Chenghao He , Fan Liu , Wenlong Liao , Tao He , Pai Peng

Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos. Existing methods struggle to distinguishing between motion and structure, particularly in scenarios where camera poses are either unknown…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Chaoyang Wang , Peiye Zhuang , Aliaksandr Siarohin , Junli Cao , Guocheng Qian , Hsin-Ying Lee , Sergey Tulyakov

We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D generation propose techniques to adapt 2D generative models for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Vikram Voleti , Chun-Han Yao , Mark Boss , Adam Letts , David Pankratz , Dmitry Tochilkin , Christian Laforte , Robin Rombach , Varun Jampani

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna

Novel View Synthesis (NVS), which tries to produce a realistic image at the target view given source view images and their corresponding poses, is a fundamental problem in 3D Vision. As this task is heavily under-constrained, some recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Shijie Li , Farhad G. Zanjani , Haitam Ben Yahia , Yuki M. Asano , Juergen Gall , Amirhossein Habibian

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

We present a novel framework for high-fidelity novel view synthesis (NVS) from sparse images, addressing key limitations in recent feed-forward 3D Gaussian Splatting (3DGS) methods built on Vision Transformer (ViT) backbones. While…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yitong Dong , Qi Zhang , Minchao Jiang , Zhiqiang Wu , Qingnan Fan , Ying Feng , Huaqi Zhang , Hujun Bao , Guofeng Zhang