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Related papers: SceneSeer: 3D Scene Design with Natural Language

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Procedural generation techniques in 3D rendering engines have revolutionized the creation of complex environments, reducing reliance on manual design. Recent approaches using Large Language Models (LLMs) for 3D scene generation show promise…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Arafa Yoncalik , Wouter Jansen , Nico Huebel , Mohammad Hasan Rahmani , Jan Steckel

We present CineVerse, a novel framework for the task of cinematic scene composition. Similar to traditional multi-shot generation, our task emphasizes the need for consistency and continuity across frames. However, our task also focuses on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Quynh Phung , Long Mai , Fabian David Caba Heilbron , Feng Liu , Jia-Bin Huang , Cusuh Ham

Recent breakthroughs in text-guided image generation have led to remarkable progress in the field of 3D synthesis from text. By optimizing neural radiance fields (NeRF) directly from text, recent methods are able to produce remarkable…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Dana Cohen-Bar , Elad Richardson , Gal Metzer , Raja Giryes , Daniel Cohen-Or

Physically based rendering is a discipline in computer graphics which aims at reproducing certain light and material appearances that occur in the real world. Complex scenes can be difficult to compute for rendering algorithms. This paper…

Graphics · Computer Science 2020-09-01 Elias Brugger , Christian Freude , Michael Wimmer

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

Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jinghao Zhou , Tomas Jakab , Philip Torr , Christian Rupprecht

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground truth information, for the purposes of…

Computer Vision and Pattern Recognition · Computer Science 2018-06-21 Chenfanfu Jiang , Siyuan Qi , Yixin Zhu , Siyuan Huang , Jenny Lin , Lap-Fai Yu , Demetri Terzopoulos , Song-Chun Zhu

Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yian Wang , Xiaowen Qiu , Jiageng Liu , Zhehuan Chen , Jiting Cai , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

Generating 3D humans that functionally interact with 3D scenes remains an open problem with applications in embodied AI, robotics, and interactive content creation. The key challenge involves reasoning about both the semantics of functional…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Jie Liu , Yu Sun , Alpar Cseke , Yao Feng , Nicolas Heron , Michael J. Black , Yan Zhang

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

In order to provide a robot with the ability to understand and react to a user's natural language inputs, the natural language must be connected to the robot's underlying representations of the world. Recently, large language models (LLMs)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Aaron Ray , Jacob Arkin , Harel Biggie , Chuchu Fan , Luca Carlone , Nicholas Roy

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

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Ian Huang , Guandao Yang , Leonidas Guibas

Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relations. Current methods often struggle to scale beyond training distribution to dense scenes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Xingjian Ran , Shujie Zhang , Weipeng Zhong , Li Luo , Bo Dai

Developing deep neural networks to generate 3D scenes is a fundamental problem in neural synthesis with immediate applications in architectural CAD, computer graphics, as well as in generating virtual robot training environments. This task…

Computer Vision and Pattern Recognition · Computer Science 2021-09-02 Haitao Yang , Zaiwei Zhang , Siming Yan , Haibin Huang , Chongyang Ma , Yi Zheng , Chandrajit Bajaj , Qixing Huang

Modern machine learning models for scene understanding, such as depth estimation and object tracking, rely on large, high-quality datasets that mimic real-world deployment scenarios. To address data scarcity, we propose an end-to-end system…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Sonia Laguna , Alberto Garcia-Garcia , Marie-Julie Rakotosaona , Stylianos Moschoglou , Leonhard Helminger , Sergio Orts-Escolano

Spatial intelligence is foundational to AI systems that interact with the physical world, particularly in 3D scene generation and spatial comprehension. Current methodologies for 3D scene generation often rely heavily on predefined…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Libin Liu , Shen Chen , Sen Jia , Jingzhe Shi , Zhongyu Jiang , Can Jin , Wu Zongkai , Jenq-Neng Hwang , Lei Li

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

3D scene understanding has gained significant attention due to its wide range of applications. However, existing methods for 3D scene understanding are limited to specific downstream tasks, which hinders their practicality in real-world…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Zehan Wang , Haifeng Huang , Yang Zhao , Ziang Zhang , Zhou Zhao