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Related papers: Indoor and Outdoor 3D Scene Graph Generation via L…

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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

This study aims to investigate the challenge of insufficient three-dimensional context in synthetic datasets for scene text rendering. Although recent advances in diffusion models and related techniques have improved certain aspects of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Li-Syun Hsiung , Jun-Kai Tu , Kuan-Wu Chu , Yu-Hsuan Chiu , Yan-Tsung Peng , Sheng-Luen Chung , Gee-Sern Jison Hsu

As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimizing a text-guided 3D model. Most of the existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Gege Gao , Weiyang Liu , Anpei Chen , Andreas Geiger , Bernhard Schölkopf

Given the steep learning curve of professional 3D software and the time-consuming process of managing large 3D assets, language-guided 3D scene editing has significant potential in fields such as virtual reality, augmented reality, and…

New era has unlocked exciting possibilities for extending Large Language Models (LLMs) to tackle 3D vision-language tasks. However, most existing 3D multimodal LLMs (MLLMs) rely on compressing holistic 3D scene information or segmenting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xiaoyan Wang , Zeju Li , Yifan Xu , Jiaxing Qi , Zhifei Yang , Ruifei Ma , Xiangde Liu , Chao Zhang

The widespread adoption of autonomous systems such as drones and assistant robots has created a need for real-time high-quality semantic scene segmentation. In this paper, we propose an efficient yet robust technique for on-the-fly dense…

Computer Vision and Pattern Recognition · Computer Science 2019-04-08 Quang-Hieu Pham , Binh-Son Hua , Duc Thanh Nguyen , Sai-Kit Yeung

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Open-vocabulary 3D scene understanding is indispensable for embodied agents. Recent works leverage pretrained vision-language models (VLMs) for object segmentation and project them to point clouds to build 3D maps. Despite progress, a point…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Zhigang Wang , Yifei Su , Chenhui Li , Dong Wang , Yan Huang , Bin Zhao , Xuelong Li

Ontologies provide formal representation of knowledge shared within Semantic Web applications. Ontology learning involves the construction of ontologies from a given corpus. In the past years, ontology learning has traversed through shallow…

Information Retrieval · Computer Science 2024-06-18 Rick Du , Huilong An , Keyu Wang , Weidong Liu

This work introduces an enhanced approach to generating scene graphs by incorporating both a relationship hierarchy and commonsense knowledge. Specifically, we begin by proposing a hierarchical relation head that exploits an informative…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Bowen Jiang , Zhijun Zhuang , Shreyas S. Shivakumar , Camillo J. Taylor

We present a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g. objects, walls, rooms), and edges represent relations (e.g.…

Robotics · Computer Science 2020-06-18 Antoni Rosinol , Arjun Gupta , Marcus Abate , Jingnan Shi , Luca Carlone

This paper introduces a novel method for open-vocabulary 3D scene querying in autonomous driving by combining Language Embedded 3D Gaussians with Large Language Models (LLMs). We propose utilizing LLMs to generate both contextually…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Amirhosein Chahe , Lifeng Zhou

Sketching in 3D space enables expressive reasoning about shape, structure, and spatial relationships, yet generating 3D sketches through natural language remains a major challenge. In this work, we introduce 3DrawAgent, a training-free,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Hongcan Xiao , Xinyue Xiao , Yilin Wang , Yue Zhang , Yonggang Qi

Autonomous navigation guided by natural language instructions is essential for improving human-robot interaction and enabling complex operations in dynamic environments. While large language models (LLMs) are not inherently designed for…

Robotics · Computer Science 2024-12-04 Pranav Doma , Aliasghar Arab , Xuesu Xiao

Creating machines capable of understanding the world in 3D is essential in assisting designers that build and edit 3D environments and robots navigating and interacting within a three-dimensional space. Inspired by advances in language and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Aadarsh Sahoo , Vansh Tibrewal , Georgia Gkioxari

Robotic tasks such as planning and navigation require a hierarchical semantic understanding of a scene, which could include multiple floors and rooms. Current methods primarily focus on object segmentation for 3D scene understanding.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yash Mehan , Kumaraditya Gupta , Rohit Jayanti , Anirudh Govil , Sourav Garg , Madhava Krishna

We present a structured graph variational autoencoder for generating the layout of indoor 3D scenes. Given the room type (e.g., living room or library) and the room layout (e.g., room elements such as floor and walls), our architecture…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Aditya Chattopadhyay , Xi Zhang , David Paul Wipf , Himanshu Arora , Rene Vidal

The rapid advancement of Large Language Models (LLMs) has resulted in interest in their potential applications within manufacturing systems, particularly in the context of Industry 5.0. However, determining when to implement LLMs versus…

Human-Computer Interaction · Computer Science 2025-05-27 John Oyekan , Christopher Turner , Michael Bax , Erich Graf

Objects and their relationships are critical contents for image understanding. A scene graph provides a structured description that captures these properties of an image. However, reasoning about the relationships between objects is very…

Computer Vision and Pattern Recognition · Computer Science 2018-11-16 Sanghyun Woo , Dahun Kim , Donghyeon Cho , In So Kweon

We present a human-centric method to sample and synthesize 3D room layouts and 2D images thereof, to obtain large-scale 2D/3D image data with perfect per-pixel ground truth. An attributed spatial And-Or graph (S-AOG) is proposed to…

Computer Vision and Pattern Recognition · Computer Science 2018-08-28 Siyuan Qi , Yixin Zhu , Siyuan Huang , Chenfanfu Jiang , Song-Chun Zhu