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Recent controllable generation approaches such as FreeControl and Diffusion Self-Guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models without training auxiliary modules. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Kuan Heng Lin , Sicheng Mo , Ben Klingher , Fangzhou Mu , Bolei Zhou

We, as human beings, can understand and picture a familiar scene from arbitrary viewpoints given a single image, whereas this is still a grand challenge for computers. We hereby present a novel solution to mimic such human perception…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Bangbang Yang , Yinda Zhang , Yijin Li , Zhaopeng Cui , Sean Fanello , Hujun Bao , Guofeng Zhang

Recent advancements in large language models (LLMs) have demonstrated remarkable text generation capabilities. However, controlling specific attributes of generated text remains challenging without architectural modifications or extensive…

Computation and Language · Computer Science 2025-11-18 Yu Li , Zhe Yang , Yi Huang , Xin Liu , Guilin Qi

The generation of high-quality 3D environments is crucial for industries such as gaming, virtual reality, and cinema, yet remains resource-intensive due to the reliance on manual processes. This study performs a systematic review of…

Graphics · Computer Science 2025-06-09 Miguel Silva , Alexandre Valle de Carvalho

Virtual Reality (VR) has emerged as a powerful tool for workforce training, offering immersive, interactive, and risk-free environments that enhance skill acquisition, decision-making, and confidence. Despite its advantages, developing VR…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Subin Raj Peter

3D scene generation plays a crucial role in gaming, artistic creation, virtual reality, and many other domains. However, current 3D scene design still relies heavily on extensive manual effort from creators, and existing automated methods…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Zixuan Bian , Ruohan Ren , Yue Yang , Chris Callison-Burch

Despite advances in indoor 3D scene layout generation, synthesizing scenes with dense object arrangements remains challenging. Existing methods focus on large furniture while neglecting smaller objects, resulting in unrealistically empty…

Graphics · Computer Science 2025-12-08 Hou In Derek Pun , Hou In Ivan Tam , Austin T. Wang , Xiaoliang Huo , Angel X. Chang , Manolis Savva

Indoor scene generation aims at creating shape-compatible, style-consistent furniture arrangements within a spatially reasonable layout. However, most existing approaches primarily focus on generating plausible furniture layouts without…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Yiqun Zhao , Zibo Zhao , Jing Li , Sixun Dong , Shenghua Gao

Image-to-3D generation faces inherent semantic ambiguity under occlusion, where partial observation alone is often insufficient to determine object category. In this work, we formalize text-driven amodal 3D generation, where text prompts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Jiayin Zhu , Guoji Fu , Xiaolu Liu , Qiyuan He , Yicong Li , Angela Yao

Recent progress in large language models (LLMs) has shown that reasoning improves when intermediate thoughts are externalized into explicit workspaces, such as chain-of-thought traces or tool-augmented reasoning. Yet, visual language models…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Oindrila Saha , Vojtech Krs , Radomir Mech , Subhransu Maji , Matheus Gadelha , Kevin Blackburn-Matzen

Automatically generating interactive 3D indoor scenes from natural language is crucial for virtual reality, gaming, and embodied AI. However, existing LLM-based approaches often suffer from spatial errors and collisions, in part because…

Artificial Intelligence · Computer Science 2026-05-01 Song Tang , Kaiyong Zhao , Yuliang Li , Qingsong Yan , Penglei Sun , Junyi Zou , Qiang Wang , Xiaowen Chu

Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined spatial relationships, limiting their capacity for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jun Luo , Jiaxiang Tang , Ruijie Lu , Gang Zeng

Video generation has achieved impressive quality, but it still suffers from artifacts such as temporal inconsistency and violation of physical laws. Leveraging 3D scenes can fundamentally resolve these issues by providing precise control…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zhaofang Qian , Abolfazl Sharifi , Tucker Carroll , Ser-Nam Lim

Large Language Models(LLMs) have revolutionized text generation and multimodal perception,but their capabilities in 3D content generation remain underexplored. Existing methods compromise by producing either low-resolution meshes or coarse…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Junming Huang , Chi Wang , Letian Li , Guangkai Xu , Donglin Huang , Hao Chen , Qiang Dai , Weiwei Xu

A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance. Staging such a scene is time-consuming and requires both artistic and technical skills. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-07-10 Kai Yan , Fujun Luan , MiloŠ HaŠAn , Thibault Groueix , Valentin Deschaintre , Shuang Zhao

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

Generating realistic 3D worlds occupied by moving humans has many applications in games, architecture, and synthetic data creation. But generating such scenes is expensive and labor intensive. Recent work generates human poses and motions…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Hongwei Yi , Chun-Hao P. Huang , Shashank Tripathi , Lea Hering , Justus Thies , Michael J. Black

Realistic 3D indoor scene datasets have enabled significant recent progress in computer vision, scene understanding, autonomous navigation, and 3D reconstruction. But the scale, diversity, and customizability of existing datasets is…

Computer Vision and Pattern Recognition · Computer Science 2021-12-13 Kai Wang , Xianghao Xu , Leon Lei , Selena Ling , Natalie Lindsay , Angel X. Chang , Manolis Savva , Daniel Ritchie

Object-level manipulation, relocating or reorienting objects in images or videos while preserving scene realism, is central to film post-production, AR, and creative editing. Yet existing methods struggle to jointly achieve three core…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Penghui Ruan , Bojia Zi , Xianbiao Qi , Youze Huang , Rong Xiao , Pichao Wang , Jiannong Cao , Yuhui Shi

Comprehending natural language instructions is a charming property for 3D indoor scene synthesis systems. Existing methods directly model object joint distributions and express object relations implicitly within a scene, thereby hindering…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Chenguo Lin , Yadong Mu