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Related papers: True Self-Supervised Novel View Synthesis is Trans…

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We study the problem of novel view synthesis from sparse source observations of a scene comprised of 3D objects. We propose a simple yet effective approach that is neither continuous nor implicit, challenging recent trends on view…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Pengsheng Guo , Miguel Angel Bautista , Alex Colburn , Liang Yang , Daniel Ulbricht , Joshua M. Susskind , Qi Shan

Diffusion models for single image novel view synthesis (NVS) can generate highly realistic and plausible images, but they are limited in the geometric consistency to the given relative poses. The generated images often show significant…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Josef Bengtson , David Nilsson , Fredrik Kahl

Currently almost all state-of-the-art novel view synthesis and reconstruction models rely on calibrated cameras or additional geometric priors for training. These prerequisites significantly limit their applicability to massive uncalibrated…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Ruoyu Wang , Yi Ma , Shenghua Gao

Existing state-of-the-art novel view synthesis methods rely on either fairly accurate 3D geometry estimation or sampling of the entire space for neural volumetric rendering, which limit the overall efficiency. In order to improve the…

Computer Vision and Pattern Recognition · Computer Science 2022-04-08 Yuemei Zhou , Tao Yu , Zerong Zheng , Ying Fu , Yebin Liu

Gaussian Splatting (GS) and Neural Radiance Fields (NeRF) are two groundbreaking technologies that have revolutionized the field of Novel View Synthesis (NVS), enabling immersive photorealistic rendering and user experiences by synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Yuhang Zhang , Joshua Maraval , Zhengyu Zhang , Nicolas Ramin , Shishun Tian , Lu Zhang

The goal of 3D pose transfer is to transfer the pose from the source mesh to the target mesh while preserving the identity information (e.g., face, body shape) of the target mesh. Deep learning-based methods improved the efficiency and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Chaoyue Song , Jiacheng Wei , Ruibo Li , Fayao Liu , Guosheng Lin

In this paper, we propose the first generalizable view synthesis approach that specifically targets multi-view stereo-camera images. Since recent stereo matching has demonstrated accurate geometry prediction, we introduce stereo matching…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Haechan Lee , Wonjoon Jin , Seung-Hwan Baek , Sunghyun Cho

We present a new approach for synthesizing novel views of people in new poses. Our novel differentiable renderer enables the synthesis of highly realistic images from any viewpoint. Rather than operating over mesh-based structures, our…

Computer Vision and Pattern Recognition · Computer Science 2022-02-22 Guillaume Rochette , Chris Russell , Richard Bowden

We present a generalizable novel view synthesis method which enables modifying the visual appearance of an observed scene so rendered views match a target weather or lighting condition without any scene specific training or access to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Josef Bengtson , David Nilsson , Che-Tsung Lin , Marcel Büsching , Fredrik Kahl

Novel View Synthesis (NVS) without Structure-from-Motion (SfM) pre-processed camera poses--referred to as SfM-free methods--is crucial for promoting rapid response capabilities and enhancing robustness against variable operating conditions.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-19 Wei Sun , Xiaosong Zhang , Fang Wan , Yanzhao Zhou , Yuan Li , Qixiang Ye , Jianbin Jiao

This work delves into the task of pose-free novel view synthesis from stereo pairs, a challenging and pioneering task in 3D vision. Our innovative framework, unlike any before, seamlessly integrates 2D correspondence matching, camera pose…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Sunghwan Hong , Jaewoo Jung , Heeseong Shin , Jiaolong Yang , Seungryong Kim , Chong Luo

Single-view novel view synthesis (NVS), the task of generating images from new viewpoints based on a single reference image, is important but challenging in computer vision. Recent advancements in NVS have leveraged Denoising Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Yifeng Xiong , Haoyu Ma , Shanlin Sun , Kun Han , Hao Tang , Xiaohui Xie

Large image diffusion models have demonstrated zero-shot capability in novel view synthesis (NVS). However, existing diffusion-based NVS methods struggle to generate novel views that are accurately consistent with the corresponding ground…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hongxiang Zhao , Xili Dai , Jianan Wang , Shengbang Tong , Jingyuan Zhang , Weida Wang , Lei Zhang , Yi Ma

Structure from motion (SfM) enables us to reconstruct a scene via casual capture from cameras at different viewpoints, and novel view synthesis (NVS) allows us to render a captured scene from a new viewpoint. Both are hard with casual…

This paper considers the problem of generative novel view synthesis (GNVS), generating novel, plausible views of a scene given a limited number of known views. Here, we propose a set-based generative model that can simultaneously generate…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Jason J. Yu , Tristan Aumentado-Armstrong , Fereshteh Forghani , Konstantinos G. Derpanis , Marcus A. Brubaker

We present a new approach for synthesizing novel views of people in new poses. Our novel differentiable renderer enables the synthesis of highly realistic images from any viewpoint. Rather than operating over mesh-based structures, our…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Guillaume Rochette , Chris Russell , Richard Bowden

This paper addresses the problem of novel view synthesis by means of neural rendering, where we are interested in predicting the novel view at an arbitrary camera pose based on a given set of input images from other viewpoints. Using the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-23 Phong Nguyen-Ha , Lam Huynh , Esa Rahtu , Janne Heikkila

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

Transfer learning of large-scale Text-to-Image (T2I) models has recently shown impressive potential for Novel View Synthesis (NVS) of diverse objects from a single image. While previous methods typically train large models on multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Yoonwoo Jeong , Jinwoo Lee , Chiheon Kim , Minsu Cho , Doyup Lee

In modern dense 3D reconstruction, feed-forward systems (e.g., VGGT, pi3) focus on end-to-end matching and geometry prediction but do not explicitly output the novel view synthesis (NVS). Neural rendering-based approaches offer…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Pengcheng Chen , Yue Hu , Wenhao Li , Nicole M Gunderson , Andrew Feng , Zhenglong Sun , Peter Beerel , Eric J Seibel