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In this paper, we propose NeoVerse, a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications. We first identify a common limitation of scalability in current 4D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yuxue Yang , Lue Fan , Ziqi Shi , Junran Peng , Feng Wang , Zhaoxiang Zhang

We introduce a recipe for generating immersive 3D worlds from a single image by framing the task as an in-context learning problem for 2D inpainting models. This approach requires minimal training and uses existing generative models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Katja Schwarz , Denys Rozumnyi , Samuel Rota Bulò , Lorenzo Porzi , Peter Kontschieder

Interactive 3D scene generation from a single image has gained significant attention due to its potential to create immersive virtual worlds. However, a key challenge in current 3D generation methods is the limited explorability, which…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Chaojun Ni , Jie Li , Haoyun Li , Hengyu Liu , Xiaofeng Wang , Zheng Zhu , Guosheng Zhao , Boyuan Wang , Chenxin Li , Guan Huang , Wenjun Mei

Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method capable of generating unbounded 3D worlds. Building upon a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Amogh Joshi , Julian Ost , Felix Heide

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

How can one efficiently generate high-quality, wide-scope 3D scenes from arbitrary single images? Existing methods suffer several drawbacks, such as requiring multi-view data, time-consuming per-scene optimization, distorted geometry in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Hanwen Liang , Junli Cao , Vidit Goel , Guocheng Qian , Sergei Korolev , Demetri Terzopoulos , Konstantinos N. Plataniotis , Sergey Tulyakov , Jian Ren

World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, scalability, and efficiency. End-to-end scene generation…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Han-Hung Lee , Cheng-Yu Yang , Yu-Lun Liu , Angel X. Chang

Existing text-to-3D and image-to-3D models often struggle with complex scenes involving multiple objects and intricate interactions. Although some recent attempts have explored such compositional scenarios, they still require an extensive…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Yujia Hu , Songhua Liu , Xingyi Yang , Xinchao Wang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

Driving scene reconstruction and rendering have advanced significantly using the 3D Gaussian Splatting. However, most prior research has focused on the rendering quality along a pre-recorded vehicle path and struggles to generalize to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jingqiu Zhou , Lue Fan , Linjiang Huang , Xiaoyu Shi , Si Liu , Zhaoxiang Zhang , Hongsheng Li

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

Generating high-quality novel views of a scene from a single image requires maintaining structural coherence across different views, referred to as view consistency. While diffusion models have driven advancements in novel view synthesis,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiwoo Park , Tae Eun Choi , Youngjun Jun , Seong Jae Hwang

We tackle the challenge of generating the infinitely extendable 3D world -- large, continuous environments with coherent geometry and realistic appearance. Existing methods face key challenges: 2D-lifting approaches suffer from geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Sikuang Li , Chen Yang , Jiemin Fang , Taoran Yi , Jia Lu , Jiazhong Cen , Lingxi Xie , Wei Shen , Qi Tian

We present Envision3D, a novel method for efficiently generating high-quality 3D content from a single image. Recent methods that extract 3D content from multi-view images generated by diffusion models show great potential. However, it is…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Yatian Pang , Tanghui Jia , Yujun Shi , Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Xing Zhou , Francis E. H. Tay , Li Yuan

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 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