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Related papers: 3D-SceneDreamer: Text-Driven 3D-Consistent Scene G…

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In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generation models to synthesize novel views, suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Shengjun Zhang , Jinzhao Li , Xin Fei , Hao Liu , Yueqi Duan

This paper presents a stylized novel view synthesis method. Applying state-of-the-art stylization methods to novel views frame by frame often causes jittering artifacts due to the lack of cross-view consistency. Therefore, this paper…

Computer Vision and Pattern Recognition · Computer Science 2022-07-07 Thu Nguyen-Phuoc , Feng Liu , Lei Xiao

Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints. We present DetailGen3D, a generative approach specifically designed to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Ken Deng , Yuan-Chen Guo , Jingxiang Sun , Zi-Xin Zou , Yangguang Li , Xin Cai , Yan-Pei Cao , Yebin Liu , Ding Liang

Recent advances in large reconstruction and generative models have significantly improved scene reconstruction and novel view generation. However, due to compute limitations, each inference with these large models is confined to a small…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangjin Zhai , Zhichao Ye , Jialin Liu , Weijian Xie , Jiaqi Hu , Zhen Peng , Hua Xue , Danpeng Chen , Xiaomeng Wang , Lei Yang , Nan Wang , Haomin Liu , Guofeng Zhang

The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we explore the use of imperfect 3D content, for instance, obtained…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Justus Thies , Michael Zollhöfer , Matthias Nießner

Generating 3D faces from textual descriptions has a multitude of applications, such as gaming, movie, and robotics. Recent progresses have demonstrated the success of unconditional 3D face generation and text-to-3D shape generation.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Cuican Yu , Guansong Lu , Yihan Zeng , Jian Sun , Xiaodan Liang , Huibin Li , Zongben Xu , Songcen Xu , Wei Zhang , Hang Xu

We present 3DScenePrompt, a framework that generates the next video chunk from arbitrary-length input while enabling precise camera control and preserving scene consistency. Unlike methods conditioned on a single image or a short clip, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 JoungBin Lee , Jaewoo Jung , Jisang Han , Takuya Narihira , Kazumi Fukuda , Junyoung Seo , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

Controllable scene synthesis consists of generating 3D information that satisfy underlying specifications. Thereby, these specifications should be abstract, i.e. allowing easy user interaction, whilst providing enough interface for detailed…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Helisa Dhamo , Fabian Manhardt , Nassir Navab , Federico Tombari

Synthetic data has been a critical tool for training scene text detection and recognition models. On the one hand, synthetic word images have proven to be a successful substitute for real images in training scene text recognizers. On the…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Shangbang Long , Cong Yao

3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging task of synthesizing multiple 3D assets within a single scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yanxu Meng , Haoning Wu , Ya Zhang , Weidi Xie

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Shijie Zhou , Zhiwen Fan , Dejia Xu , Haoran Chang , Pradyumna Chari , Tejas Bharadwaj , Suya You , Zhangyang Wang , Achuta Kadambi

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

In this system, we discuss methods to stylize a scene of 3D primitive objects into a higher fidelity 3D scene using novel 3D representations like NeRFs and 3D Gaussian Splatting. Our approach leverages existing image stylization systems and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Yuanbo Chen , Yixiao Kang , Yukun Song , Cyrus Vachha , Sining Huang

Text-to-3D generation has achieved remarkable success via large-scale text-to-image diffusion models. Nevertheless, there is no paradigm for scaling up the methodology to urban scale. Urban scenes, characterized by numerous elements,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Fan Lu , Kwan-Yee Lin , Yan Xu , Hongsheng Li , Guang Chen , Changjun Jiang

Neural rendering has garnered substantial attention owing to its capacity for creating realistic 3D scenes. However, its applicability to extensive scenes remains challenging, with limitations in effectiveness. In this work, we propose the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Zhihao Jia , Bing Wang , Changhao Chen

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma

Scene-consistent video generation aims to create videos that explore 3D scenes based on a camera trajectory. Previous methods rely on video generation models with external memory for consistency, or iterative 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 JiaKui Hu , Jialun Liu , Liying Yang , Xinliang Zhang , Kaiwen Li , Shuang Zeng , Yuanwei Li , Haibin Huang , Chi Zhang , Yanye Lu

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark contrast to the easiness with which people can use language…

Graphics · Computer Science 2017-03-02 Angel X. Chang , Mihail Eric , Manolis Savva , Christopher D. Manning