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Related papers: SLayR: Scene Layout Generation with Rectified Flow

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The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Generating realistic 3D scenes from text is crucial for immersive applications like VR, AR, and gaming. While text-driven approaches promise efficiency, existing methods suffer from limited 3D-text data and inconsistent multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Xin Zhang , Shen Chen , Jiale Zhou , Lei Li

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Jiaxin Cheng , Zixu Zhao , Tong He , Tianjun Xiao , Yicong Zhou , Zheng Zhang

How does audio describe the world around us? In this paper, we propose a method for generating an image of a scene from sound. Our method addresses the challenges of dealing with the large gaps that often exist between sight and sound. We…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Kim Sung-Bin , Arda Senocak , Hyunwoo Ha , Andrew Owens , Tae-Hyun Oh

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus on character consistency, they often overlook the crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanjian Song , Donghao Zhou , Jingyu Lin , Fei Shen , Jiaze Wang , Xiaowei Hu , Cunjian Chen , Pheng-Ann Heng

Generating realistic building layouts for automatic building design has been studied in both the computer vision and architecture domains. Traditional approaches from the architecture domain, which are based on optimization techniques or…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jiachen Liu , Yuan Xue , Haomiao Ni , Rui Yu , Zihan Zhou , Sharon X. Huang

Recent works have demonstrated success in controlling sentence attributes ($e.g.$, sentiment) and structure ($e.g.$, syntactic structure) based on the diffusion language model. A key component that drives theimpressive performance for…

Computation and Language · Computer Science 2024-03-26 Shujian Zhang , Lemeng Wu , Chengyue Gong , Xingchao Liu

Autoregressive (AR) modeling has achieved remarkable success in natural language processing by enabling models to generate text with coherence and contextual understanding through next token prediction. Recently, in image generation, VAR…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Sucheng Ren , Qihang Yu , Ju He , Xiaohui Shen , Alan Yuille , Liang-Chieh Chen

Advancements in generative models have sparked significant interest in generating images while adhering to specific structural guidelines. Scene graph to image generation is one such task of generating images which are consistent with the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Rameshwar Mishra , A V Subramanyam

Synthesizing interactive 3D scenes from text is essential for gaming, virtual reality, and embodied AI. However, existing methods face several challenges. Learning-based approaches depend on small-scale indoor datasets, limiting the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Lu Ling , Chen-Hsuan Lin , Tsung-Yi Lin , Yifan Ding , Yu Zeng , Yichen Sheng , Yunhao Ge , Ming-Yu Liu , Aniket Bera , Zhaoshuo Li

We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute constraints between layout elements as edges in the layout…

Computer Vision and Pattern Recognition · Computer Science 2020-11-30 Wamiq Para , Paul Guerrero , Tom Kelly , Leonidas Guibas , Peter Wonka

NeRF provides unparalleled fidelity of novel view synthesis: rendering a 3D scene from an arbitrary viewpoint. NeRF requires training on a large number of views that fully cover a scene, which limits its applicability. While these issues…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Pol Moreno , Adam R. Kosiorek , Heiko Strathmann , Daniel Zoran , Rosalia G. Schneider , Björn Winckler , Larisa Markeeva , Théophane Weber , Danilo J. Rezende

Design generation, in its essence, is a step-by-step process where designers progressively refine and enhance their work through careful modifications. Despite this fundamental characteristic, existing approaches mainly treat design…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Faizan Farooq Khan , K J Joseph , Koustava Goswami , Mohamed Elhoseiny , Balaji Vasan Srinivasan

Graphic design images consist of multiple editable layers, such as text, background, and decorative elements, while most generative models produce rasterized outputs without explicit layer structures, limiting downstream editing. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Weidong Chen , Dexiang Hong , Zhendong Mao , Yutao Cheng , Xinyan Liu , Lei Zhang , Yongdong Zhang

Most of the existing works on image description focus on generating expressive descriptions. The only few works that are dedicated to generating stylish (e.g., romantic, lyric, etc.) descriptions suffer from limited style variation and…

Computer Vision and Pattern Recognition · Computer Science 2018-09-18 Cheng Kuan Chen , Zhu Feng Pan , Min Sun , Ming-Yu Liu

Recent advancements in Generative Artificial Intelligence (GenAI) have significantly enhanced the capabilities of both image generation and editing. However, current approaches often treat these tasks separately, leading to inefficiencies…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Thanh-Nhan Vo , Trong-Thuan Nguyen , Tam V. Nguyen , Minh-Triet Tran

Building LiDAR generative models holds promise as powerful data priors for restoration, scene manipulation, and scalable simulation in autonomous mobile robots. In recent years, approaches using diffusion models have emerged, significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Kazuto Nakashima , Xiaowen Liu , Tomoya Miyawaki , Yumi Iwashita , Ryo Kurazume

In recent years, advancements in AIGC (Artificial Intelligence Generated Content) technology have significantly enhanced the capabilities of large text-to-image models. Despite these improvements, controllable image generation remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Bowen Zhang , Cheng Yang , Xuanhui Liu

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

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson
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