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In this paper we present a technique for procedurally generating 3D maps using a set of premade meshes which snap together based on designer-specified visual constraints. The proposed approach avoids size and layout limitations, offering…

Artificial Intelligence · Computer Science 2022-05-03 Rafael C. e Silva , Nuno Fachada , Diogo de Andrade , Nélio Códices

Bird's-Eye View (BEV) features are popular intermediate scene representations shared by the 3D backbone and the detector head in LiDAR-based object detectors. However, little research has been done to investigate how to incorporate…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Haitao Yang , Zaiwei Zhang , Xiangru Huang , Min Bai , Chen Song , Bo Sun , Li Erran Li , Qixing Huang

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

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes is inherently inaccurate and lacks fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Minglin Chen , Longguang Wang , Sheng Ao , Ye Zhang , Kai Xu , Yulan Guo

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

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Synthesizing photo-realistic visual observations from an ego vehicle's driving trajectory is a critical step towards scalable training of self-driving models. Reconstruction-based methods create 3D scenes from driving logs and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Jiageng Mao , Boyi Li , Boris Ivanovic , Yuxiao Chen , Yan Wang , Yurong You , Chaowei Xiao , Danfei Xu , Marco Pavone , Yue Wang

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

Diffusion models have shown remarkable results in generating 2D images and small-scale 3D objects. However, their application to the synthesis of large-scale 3D scenes has been rarely explored. This is mainly due to the inherent complexity…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Yuheng Liu , Xinke Li , Xueting Li , Lu Qi , Chongshou Li , Ming-Hsuan Yang

We present LT3SD, a novel latent diffusion model for large-scale 3D scene generation. Recent advances in diffusion models have shown impressive results in 3D object generation, but are limited in spatial extent and quality when extended to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Quan Meng , Lei Li , Matthias Nießner , Angela Dai

3D scene graphs have recently emerged as a powerful high-level representation of 3D environments. A 3D scene graph describes the environment as a layered graph where nodes represent spatial concepts at multiple levels of abstraction and…

Robotics · Computer Science 2022-06-22 Nathan Hughes , Yun Chang , Luca Carlone

Understanding a visual scene goes beyond recognizing individual objects in isolation. Relationships between objects also constitute rich semantic information about the scene. In this work, we explicitly model the objects and their…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Danfei Xu , Yuke Zhu , Christopher B. Choy , Li Fei-Fei

Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generated on top of objects detected in an image with their pairwise…

Computer Vision and Pattern Recognition · Computer Science 2017-09-18 Yikang Li , Wanli Ouyang , Bolei Zhou , Kun Wang , Xiaogang Wang

Diffusion models (DMs) excel in photo-realistic image synthesis, but their adaptation to LiDAR scene generation poses a substantial hurdle. This is primarily because DMs operating in the point space struggle to preserve the curve-like…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Haoxi Ran , Vitor Guizilini , Yue Wang

We present SceneFactor, a diffusion-based approach for large-scale 3D scene generation that enables controllable generation and effortless editing. SceneFactor enables text-guided 3D scene synthesis through our factored diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Alexey Bokhovkin , Quan Meng , Shubham Tulsiani , Angela Dai

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

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 explore the task of generating expansive outdoor scenes, ranging from castles to high-rises. Unlike indoor scene generation, which has been a primary focus of prior work, outdoor scene generation presents unique…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Han-Hung Lee , Qinghong Han , Angel X. Chang

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

We present EchoScene, an interactive and controllable generative model that generates 3D indoor scenes on scene graphs. EchoScene leverages a dual-branch diffusion model that dynamically adapts to scene graphs. Existing methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Guangyao Zhai , Evin Pınar Örnek , Dave Zhenyu Chen , Ruotong Liao , Yan Di , Nassir Navab , Federico Tombari , Benjamin Busam
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