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Related papers: Toward Scene Graph and Layout Guided Complex 3D Sc…

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Scene-graph generation involves creating a structural representation of the relationships between objects in a scene by predicting subject-object-relation triplets from input data. Existing methods show poor performance in detecting…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 A S M Iftekhar , Raphael Ruschel , Satish Kumar , Suya You , B. S. Manjunath

Comprehending natural language instructions is a charming property for both 2D and 3D layout synthesis systems. Existing methods implicitly model object joint distributions and express object relations, hindering generation's…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Chenguo Lin , Yuchen Lin , Panwang Pan , Xuanyang Zhang , Yadong Mu

In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable of producing high-fidelity shapes with colors that match the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhengzhe Liu , Yi Wang , Xiaojuan Qi , Chi-Wing Fu

Recent approaches on visual scene understanding attempt to build a scene graph -- a computational representation of objects and their pairwise relationships. Such rich semantic representation is very appealing, yet difficult to obtain from…

Computer Vision and Pattern Recognition · Computer Science 2018-11-08 Paul Gay , Stuart James , Alessio Del Bue

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

Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Haoran Li , Haolin Shi , Wenli Zhang , Wenjun Wu , Yong Liao , Lin Wang , Lik-hang Lee , Pengyuan Zhou

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Oran Gafni , Adam Polyak , Oron Ashual , Shelly Sheynin , Devi Parikh , Yaniv Taigman

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

Scene graph alignment establishes object correspondences between two 3D scene graphs constructed from partially overlapping observations. This enables efficient scene understanding and object-level relocalization when a robot revisits a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Gang Chen , Sebastián Barbas Laina , Stefan Leutenegger , Javier Alonso-Mora

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

In this paper, we present a novel method for 3D geometric scene graph generation using range sensors and RGB cameras. We initially detect instance-wise keypoints with a YOLOv8s model to compute 6D pose estimates of known objects by solving…

Robotics · Computer Science 2024-08-12 Lennart Niecksch , Alexander Mock , Felix Igelbrink , Thomas Wiemann , Joachim Hertzberg

In this paper, we propose a new framework for zero-shot object navigation. Existing zero-shot object navigation methods prompt LLM with the text of spatially closed objects, which lacks enough scene context for in-depth reasoning. To better…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Hang Yin , Xiuwei Xu , Zhenyu Wu , Jie Zhou , Jiwen Lu

Research in scene graph generation has quickly gained traction in the past few years because of its potential to help in downstream tasks like visual question answering, image captioning, etc. Many interesting approaches have been proposed…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Sandeep Inuganti , Vineeth N Balasubramanian

Generative models have shown great promise in synthesizing photorealistic 3D objects, but they require large amounts of training data. We introduce SinGRAF, a 3D-aware generative model that is trained with a few input images of a single…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Minjung Son , Jeong Joon Park , Leonidas Guibas , Gordon Wetzstein

Our project page: https://scutyklin.github.io/SceneLCM/. Automated generation of complex, interactive indoor scenes tailored to user prompt remains a formidable challenge. While existing methods achieve indoor scene synthesis, they struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yangkai Lin , Jiabao Lei , Kui Jia

Scene graph generation (SGG) endeavors to predict visual relationships between pairs of objects within an image. Prevailing SGG methods traditionally assume a one-off learning process for SGG. This conventional paradigm may necessitate…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Tao He , Tongtong Wu , Dongyang Zhang , Guiduo Duan , Ke Qin , Yuan-Fang Li

Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks. This work proposes a method to incrementally build up semantic scene graphs from a 3D environment given a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Shun-Cheng Wu , Johanna Wald , Keisuke Tateno , Nassir Navab , Federico Tombari

3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further increased interest in this area. Existing methods broadly follow…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haozhi Zhu , Miaomiao Zhao , Dingyao Liu , Runze Tian , Yan Zhang , Jie Guo , Fenggen Yu

3D semantic scene graphs are a powerful holistic representation as they describe the individual objects and depict the relation between them. They are compact high-level graphs that enable many tasks requiring scene reasoning. In real-world…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Shun-Cheng Wu , Keisuke Tateno , Nassir Navab , Federico Tombari