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Related papers: MVRoom: Controllable 3D Indoor Scene Generation wi…

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We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

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

Novel View Synthesis (NVS) aims to generate unseen views of a 3D object given a limited number of known views. Existing methods often struggle to synthesize plausible views for unobserved regions, particularly under single-view input, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Jinglin Liang , Zijian Zhou , Rui Huang , Shuangping Huang , Yichen Gong

Spatial control methods using additional modules on pretrained diffusion models have gained attention for enabling conditional generation in natural images. These methods guide the generation process with new conditions while leveraging the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Suhyun Ahn , Wonjung Park , Jihoon Cho , Seunghyuck Park , Jinah Park

We present Stable View Synthesis (SVS). Given a set of source images depicting a scene from freely distributed viewpoints, SVS synthesizes new views of the scene. The method operates on a geometric scaffold computed via…

Computer Vision and Pattern Recognition · Computer Science 2021-05-04 Gernot Riegler , Vladlen Koltun

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are…

We address the problem of novel view synthesis (NVS) from a few sparse source view images. Conventional image-based rendering methods estimate scene geometry and synthesize novel views in two separate steps. However, erroneous geometry…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Yujiao Shi , Hongdong Li , Xin Yu

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

In this paper, we propose an approach for synthesizing novel view images from a single RGBD (Red Green Blue-Depth) input. Novel view synthesis (NVS) is an interesting computer vision task with extensive applications. Methods using multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Congrui Hetang , Yuping Wang

We present SemanticNVS, a camera-conditioned multi-view diffusion model for novel view synthesis (NVS), which improves generation quality and consistency by integrating pre-trained semantic feature extractors. Existing NVS methods perform…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Xinya Chen , Christopher Wewer , Jiahao Xie , Xinting Hu , Jan Eric Lenssen

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to generate a 3D model, which lacks the control of each…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Peng Li , Suizhi Ma , Jialiang Chen , Yuan Liu , Congyi Zhang , Wei Xue , Wenhan Luo , Alla Sheffer , Wenping Wang , Yike Guo

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data. However, existing methods depend on external multi-view alignment processes, such as explicit pose estimation or…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Lingen Li , Zhaoyang Zhang , Yaowei Li , Jiale Xu , Wenbo Hu , Xiaoyu Li , Weihao Cheng , Jinwei Gu , Tianfan Xue , Ying Shan

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achieve this, we use a monocular depth estimator that transfers…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Yash Kant , Aliaksandr Siarohin , Michael Vasilkovsky , Riza Alp Guler , Jian Ren , Sergey Tulyakov , Igor Gilitschenski

We introduce VividDream, a method for generating explorable 4D scenes with ambient dynamics from a single input image or text prompt. VividDream first expands an input image into a static 3D point cloud through iterative inpainting and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yao-Chih Lee , Yi-Ting Chen , Andrew Wang , Ting-Hsuan Liao , Brandon Y. Feng , Jia-Bin Huang

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

We present a portable multiscopic camera system with a dedicated model for novel view and time synthesis in dynamic scenes. Our goal is to render high-quality images for a dynamic scene from any viewpoint at any time using our portable…

Computer Vision and Pattern Recognition · Computer Science 2022-08-31 Tianjia Zhang , Yuen-Fui Lau , Qifeng Chen

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and the lack of robust global structural priors caused by limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Wenyue Chen , Wenjue Chen , Peng Li , Qinghe Wang , Xu Jia , Heliang Zheng , Rongfei Jia , Yuan Liu , Ronggang Wang
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