English
Related papers

Related papers: ZeroScene: A Zero-Shot Framework for 3D Scene Gene…

200 papers

Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of objects. This work presents DisCoScene: a 3Daware generative…

Computer Vision and Pattern Recognition · Computer Science 2022-12-23 Yinghao Xu , Menglei Chai , Zifan Shi , Sida Peng , Ivan Skorokhodov , Aliaksandr Siarohin , Ceyuan Yang , Yujun Shen , Hsin-Ying Lee , Bolei Zhou , Sergey Tulyakov

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

Text-to-Image (T2I) diffusion models have recently gained traction for their versatility and user-friendliness in 2D content generation and editing. However, training a diffusion model specifically for 3D scene editing is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Nazmul Karim , Hasan Iqbal , Umar Khalid , Jing Hua , Chen Chen

Digitizing the physical world into accurate simulation-ready virtual environments offers significant opportunities in a variety of fields such as augmented and virtual reality, gaming, and robotics. However, current 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Hongchi Xia , Chih-Hao Lin , Hao-Yu Hsu , Quentin Leboutet , Katelyn Gao , Michael Paulitsch , Benjamin Ummenhofer , Shenlong Wang

We present ZeroComp, an effective zero-shot 3D object compositing approach that does not require paired composite-scene images during training. Our method leverages ControlNet to condition from intrinsic images and combines it with a Stable…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Zitian Zhang , Frédéric Fortier-Chouinard , Mathieu Garon , Anand Bhattad , Jean-François Lalonde

The scarcity of free-hand sketch presents a challenging problem. Despite the emergence of some large-scale sketch datasets, these datasets primarily consist of sketches at the single-object level. There continues to be a lack of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhenbei Wu , Qiang Wang , Jie Yang

Can we synthesize 3D humans interacting with scenes without learning from any 3D human-scene interaction data? We propose GenZI, the first zero-shot approach to generating 3D human-scene interactions. Key to GenZI is our distillation of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Lei Li , Angela Dai

3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, creating temporally consistent and realistic textures for mesh…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Jingzhi Bao , Xueting Li , Ming-Hsuan Yang

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

Human-scene interaction (HSI) generation is crucial for applications in embodied AI, virtual reality, and robotics. Yet, existing methods cannot synthesize interactions in unseen environments such as in-the-wild scenes or reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Hongjie Li , Hong-Xing Yu , Jiaman Li , Jiajun Wu

Humans can naturally identify and mentally complete occluded objects in cluttered environments. However, imparting similar cognitive ability to robotics remains challenging even with advanced reconstruction techniques, which models scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zesong Yang , Bangbang Yang , Wenqi Dong , Chenxuan Cao , Liyuan Cui , Yuewen Ma , Zhaopeng Cui , Hujun Bao

Traditional 3D scene understanding approaches rely on labeled 3D datasets to train a model for a single task with supervision. We propose OpenScene, an alternative approach where a model predicts dense features for 3D scene points that are…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Songyou Peng , Kyle Genova , Chiyu "Max" Jiang , Andrea Tagliasacchi , Marc Pollefeys , Thomas Funkhouser

Generative models have shown substantial impact across multiple domains, their potential for scene synthesis remains underexplored in robotics. This gap is more evident in drone simulators, where simulation environments still rely heavily…

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

High-quality 3D scene generation from a single image is crucial for AR/VR and embodied AI applications. Early approaches struggle to generalize due to reliance on specialized models trained on curated small datasets. While recent…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Boshi Tang , Henry Zheng , Rui Huang , Gao Huang

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Guangyao Zhai , Evin Pınar Örnek , Shun-Cheng Wu , Yan Di , Federico Tombari , Nassir Navab , Benjamin Busam

The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple single-view image. However, due to the partial priors provided by single-view input, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Tianyi Gong , Boyan Li , Yifei Zhong , Fangxin Wang

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

In this paper, we introduce \textit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for single-view scene reconstruction typically rely on object retrieval or the regression…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yuhan Ping , Yuan Liu , Xiaoxiao Long , Peng Wang , Junhui Hou , Jianyi Zheng , Jia Pan , Xin Li , Cheng Lin

3D editing has shown remarkable capability in editing scenes based on various instructions. However, existing methods struggle with achieving intuitive, localized editing, such as selectively making flowers blossom. Drag-style editing has…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Chenghao Gu , Zhenzhe Li , Zhengqi Zhang , Yunpeng Bai , Shuzhao Xie , Zhi Wang