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Related papers: Scene-Conditional 3D Object Stylization and Compos…

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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

Image editing approaches have become more powerful and flexible with the advent of powerful text-conditioned generative models. However, placing objects in an environment with a precise location and orientation still remains a challenge, as…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Mohamed Omran , Dimitris Kalatzis , Jens Petersen , Amirhossein Habibian , Auke Wiggers

In this work, we introduce CC3D, a conditional generative model that synthesizes complex 3D scenes conditioned on 2D semantic scene layouts, trained using single-view images. Different from most existing 3D GANs that limit their…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Sherwin Bahmani , Jeong Joon Park , Despoina Paschalidou , Xingguang Yan , Gordon Wetzstein , Leonidas Guibas , Andrea Tagliasacchi

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hui Shan , Keyang Luo , Ming Li , Sizhe Zheng , Yanwei Fu , Zhen Chen , Xiangru Huang

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow generation to generate realistic results. Furthermore,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Yizhi Song , Zhifei Zhang , Zhe Lin , Scott Cohen , Brian Price , Jianming Zhang , Soo Ye Kim , Daniel Aliaga

In this system, we discuss methods to stylize a scene of 3D primitive objects into a higher fidelity 3D scene using novel 3D representations like NeRFs and 3D Gaussian Splatting. Our approach leverages existing image stylization systems and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Yuanbo Chen , Yixiao Kang , Yukun Song , Cyrus Vachha , Sining Huang

We present Style3D, a novel approach for generating stylized 3D objects from a content image and a style image. Unlike most previous methods that require case- or style-specific training, Style3D supports instant 3D object stylization. Our…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Bingjie Song , Xin Huang , Ruting Xie , Xue Wang , Qing Wang

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

Generating 3D visual scenes is at the forefront of visual generative AI, but current 3D generation techniques struggle with generating scenes with multiple high-resolution objects. Here we introduce Lay-A-Scene, which solves the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ohad Rahamim , Hilit Segev , Idan Achituve , Yuval Atzmon , Yoni Kasten , Gal Chechik

With the onset of diffusion-based generative models and their ability to generate text-conditioned images, content generation has received a massive invigoration. Recently, these models have been shown to provide useful guidance for the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Alexander Vilesov , Pradyumna Chari , Achuta Kadambi

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

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

We address the problem of multi-object 3D pose control in image diffusion models. Instead of conditioning on a sequence of text tokens, we propose to use a set of per-object representations, Neural Assets, to control the 3D pose of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Ziyi Wu , Yulia Rubanova , Rishabh Kabra , Drew A. Hudson , Igor Gilitschenski , Yusuf Aytar , Sjoerd van Steenkiste , Kelsey R. Allen , Thomas Kipf

We present DiffuScene for indoor 3D scene synthesis based on a novel scene configuration denoising diffusion model. It generates 3D instance properties stored in an unordered object set and retrieves the most similar geometry for each…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Jiapeng Tang , Yinyu Nie , Lev Markhasin , Angela Dai , Justus Thies , Matthias Nießner

Generative models have achieved significant progress in advancing 2D image editing, demonstrating exceptional precision and realism. However, they often struggle with consistency and object identity preservation due to their inherent…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuhuan Xie , Aoxuan Pan , Ming-Xian Lin , Wei Huang , Yi-Hua Huang , Xiaojuan Qi

3D scene stylization refers to transform the appearance of a 3D scene to match a given style image, ensuring that images rendered from different viewpoints exhibit the same style as the given style image, while maintaining the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Jiafu Chen , Wei Xing , Jiakai Sun , Tianyi Chu , Yiling Huang , Boyan Ji , Lei Zhao , Huaizhong Lin , Haibo Chen , Zhizhong Wang

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
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