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Related papers: PhiP-G: Physics-Guided Text-to-3D Compositional Sc…

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Accurate interpretation and visual representation of complex prompts involving multiple objects, attributes, and spatial relationships is a critical challenge in text-to-image synthesis. Despite recent advancements in generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Hirunima Jayasekara , Chuong Huynh , Yixuan Ren , Christabel Acquaye , Abhinav Shrivastava

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

Scene graphs provide valuable information to many downstream tasks. Many scene graph generation (SGG) models solely use the limited annotated relation triples for training, leading to their underperformance on low-shot (few and zero)…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Tao He , Lianli Gao , Jingkuan Song , Jianfei Cai , Yuan-Fang Li

The latest emerged 4D Panoptic Scene Graph (4D-PSG) provides an advanced-ever representation for comprehensively modeling the dynamic 4D visual real world. Unfortunately, current pioneering 4D-PSG research can primarily suffer from data…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Shengqiong Wu , Hao Fei , Jingkang Yang , Xiangtai Li , Juncheng Li , Hanwang Zhang , Tat-seng Chua

Content creators often draw inspiration from multiple visual sources, combining distinct elements to craft new compositions. Modern computational approaches now aim to emulate this fundamental creative process. Although recent diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Sara Dorfman , Dana Cohen-Bar , Rinon Gal , Daniel Cohen-Or

The ability to map descriptions of scenes to 3D geometric representations has many applications in areas such as art, education, and robotics. However, prior work on the text to 3D scene generation task has used manually specified object…

Computation and Language · Computer Science 2015-06-08 Angel Chang , Will Monroe , Manolis Savva , Christopher Potts , Christopher D. Manning

Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing complex scenes with multiple objects. While excelling in…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Hanan Gani , Shariq Farooq Bhat , Muzammal Naseer , Salman Khan , Peter Wonka

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

Scene graphs (SGs) represent objects and their relationships as structured graphs, enabling applications in image generation, robotics, and 3D understanding. Recent work suggests that conditioning image generation on scene graphs improves…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Rajalaxmi Rajagopalan , Romit Roy Choudhury

Recent advances in 3D generative models have rapidly improved image-to-3D synthesis quality, enabling higher-resolution geometry and more realistic appearance. Yet fidelity, which measures pixel-level faithfulness of the generated 3D asset…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Dong-Yang Li , Wang Zhao , Yuxin Chen , Wenbo Hu , Meng-Hao Guo , Fang-Lue Zhang , Ying Shan , Shi-Min Hu

Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-world multi-object environments. Conventional works typically…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yao Wei , Martin Renqiang Min , George Vosselman , Li Erran Li , Michael Ying Yang

Existing generative approaches for guided image synthesis of multi-object scenes typically rely on 2D controls in the image or text space. As a result, these methods struggle to maintain and respect consistent three-dimensional geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Léopold Maillard , Tom Durand , Adrien Ramanana Rahary , Maks Ovsjanikov

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

Prompt-driven scene synthesis allows users to generate complete 3D environments from textual descriptions. Current text-to-scene methods often struggle with complex geometries and object transformations, and tend to show weak adherence to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Frédéric Berdoz , Luca A. Lanzendörfer , Nick Tuninga , Roger Wattenhofer

Text-to-image diffusion models exhibit remarkable generative capabilities, but lack precise control over object counts and spatial arrangements. This work introduces a two-stage system to address these compositional limitations. The first…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Jan-Hendrik Koch , Jonas Krumme , Konrad Gadzicki

Text-to-3D generation represents an exciting field that has seen rapid advancements, facilitating the transformation of textual descriptions into detailed 3D models. However, current progress often neglects the intricate high-order…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Donglin Di , Jiahui Yang , Chaofan Luo , Zhou Xue , Wei Chen , Xun Yang , Yue Gao

Real-world meal images often contain multiple food items, making reliable compositional food image generation important for applications such as image-based dietary assessment, where multi-food data augmentation is needed, and recipe…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Xinyue Pan , Yuhao Chen , Fengqing Zhu

Recent advances in large language models (LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in procedural content generation (PCG). We present a lightweight…

Graphics · Computer Science 2026-01-05 Yi-Chun Chen , Arnav Jhala

For an artist or a graphic designer, the spatial layout of a scene is a critical design choice. However, existing text-to-image diffusion models provide limited support for incorporating spatial information. This paper introduces Composite…

Computer Vision and Pattern Recognition · Computer Science 2023-07-27 Vikram Jamwal , Ramaneswaran S

Realistic 3D indoor scene generation is crucial for virtual reality, interior design, embodied intelligence, and scene understanding. While existing methods have made progress in coarse-scale furniture arrangement, they struggle to capture…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Xiping Wang , Yuxi Wang , Mengqi Zhou , Junsong Fan , Zhaoxiang Zhang