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We introduce \textit{WonderVerse}, a simple but effective framework for generating extendable 3D scenes. Unlike existing methods that rely on iterative depth estimation and image inpainting, often leading to geometric distortions and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Hao Feng , Zhi Zuo , Jia-Hui Pan , Ka-Hei Hui , Qi Dou , Jingyu Hu , Zhengzhe Liu

Generating multi-camera street-view videos is critical for augmenting autonomous driving datasets, addressing the urgent demand for extensive and varied data. Due to the limitations in diversity and challenges in handling lighting…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jiachen Lu , Ze Huang , Zeyu Yang , Jiahui Zhang , Li Zhang

We present DiffInDScene, a novel framework for tackling the problem of high-quality 3D indoor scene generation, which is challenging due to the complexity and diversity of the indoor scene geometry. Although diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Xiaoliang Ju , Zhaoyang Huang , Yijin Li , Guofeng Zhang , Yu Qiao , Hongsheng Li

Transparent image layer generation plays a significant role in digital art and design workflows. Existing methods typically decompose transparent layers from a single RGB image using a set of tools or generate multiple transparent layers…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Dingbang Huang , Wenbo Li , Yifei Zhao , Xinyu Pan , Chun Wang , Yanhong Zeng , Bo Dai

Real-world scenes, such as those in ScanNet, are difficult to capture, with highly limited data available. Generating realistic scenes with varied object poses remains an open and challenging task. In this work, we propose FactoredScenes, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Joy Hsu , Emily Jin , Jiajun Wu , Niloy J. Mitra

Generating 3D scenes is still a challenging task due to the lack of readily available scene data. Most existing methods only produce partial scenes and provide limited navigational freedom. We introduce a practical and scalable solution…

Graphics · Computer Science 2025-09-26 Zhaoyang Zhang , Yannick Hold-Geoffroy , Miloš Hašan , Ziwen Chen , Fujun Luan , Julie Dorsey , Yiwei Hu

As generative models expand the possibilities of visual content creation, layered image synthesis has emerged as a promising direction for controllable and creative editing. However, existing methods struggle to fully realize this…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Kyoungkook Kang , Gyujin Sim , Sunghyun Cho

Generating unbounded 3D scenes is crucial for large-scale scene understanding and simulation. Urban scenes, unlike natural landscapes, consist of various complex man-made objects and structures such as roads, traffic signs, vehicles, and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Junge Zhang , Qihang Zhang , Li Zhang , Ramana Rao Kompella , Gaowen Liu , Bolei Zhou

In this paper, we address the problem of conditional scene decoration for 360-degree images. Our method takes a 360-degree background photograph of an indoor scene and generates decorated images of the same scene in the panorama view. To do…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Ka Chun Shum , Hong-Wing Pang , Binh-Son Hua , Duc Thanh Nguyen , Sai-Kit Yeung

Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing consistent 3D scenes from these outputs remains challenging, due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yisu Zhang , Chenjie Cao , Tengfei Wang , Xuhui Zuo , Junta Wu , Jianke Zhu , Chunchao Guo

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certain attributes within a generated image. Although successful,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Jonghyun Lee , Hansam Cho , Youngjoon Yoo , Seoung Bum Kim , Yonghyun Jeong

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

We present WonderWorld, a novel framework for interactive 3D scene generation that enables users to interactively specify scene contents and layout and see the created scenes in low latency. The major challenge lies in achieving fast…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Hong-Xing Yu , Haoyi Duan , Charles Herrmann , William T. Freeman , Jiajun Wu

In this work, we present SceneDreamer, an unconditional generative model for unbounded 3D scenes, which synthesizes large-scale 3D landscapes from random noise. Our framework is learned from in-the-wild 2D image collections only, without…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Zhaoxi Chen , Guangcong Wang , Ziwei Liu

Furnishing and rendering indoor scenes has been a long-standing task for interior design, where artists create a conceptual design for the space, build a 3D model of the space, decorate, and then perform rendering. Although the task is…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Hong-Wing Pang , Yingshu Chen , Phuoc-Hieu Le , Binh-Son Hua , Duc Thanh Nguyen , Sai-Kit Yeung

Prompt-driven scene synthesis allows users to generate complete 3D environments from textual descriptions. Current text-to-scene methods often struggle with complex geometries and object transformations, and tend to show weak adherence to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Frédéric Berdoz , Luca A. Lanzendörfer , Nick Tuninga , Roger Wattenhofer

The crux of text-to-image synthesis stems from the difficulty of preserving the cross-modality semantic consistency between the input text and the synthesized image. Typical methods, which seek to model the text-to-image mapping directly,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-15 Jiadong Liang , Wenjie Pei , Feng Lu

Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jinghao Zhou , Tomas Jakab , Philip Torr , Christian Rupprecht

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

The reconstruction of immersive and realistic 3D scenes holds significant practical importance in various fields of computer vision and computer graphics. Typically, immersive and realistic scenes should be free from obstructions by dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Zilong Huang , Jun He , Junyan Ye , Lihan Jiang , Weijia Li , Yiping Chen , Ting Han