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Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that mesh reconstruction fails on. However, these methods entangle…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 Fanbo Xiang , Zexiang Xu , Miloš Hašan , Yannick Hold-Geoffroy , Kalyan Sunkavalli , Hao Su

Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-video models to generate dynamic 3D scenes. However, current text-to-4D methods face a three-way tradeoff between the quality of scene appearance,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Sherwin Bahmani , Ivan Skorokhodov , Victor Rong , Gordon Wetzstein , Leonidas Guibas , Peter Wonka , Sergey Tulyakov , Jeong Joon Park , Andrea Tagliasacchi , David B. Lindell

Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applications such as immersive interaction and content creation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiaoxuan Ma , Jiashun Wang , Nicolas Ugrinovic , Yehonathan Litman , Kris Kitani

Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instance-level control to text-to-image diffusion models.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Xudong Wang , Trevor Darrell , Sai Saketh Rambhatla , Rohit Girdhar , Ishan Misra

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly dependent on the accuracy of this "scene-space" information. We…

Computer Vision and Pattern Recognition · Computer Science 2021-02-08 Felix Klose , Oliver Wang , Jean-Charles Bazin , Marcus Magnor , Alexander Sorkine-Hornung

3D indoor scene generation is an important problem for the design of digital and real-world environments. To automate this process, a scene generation model should be able to not only generate plausible scene layouts, but also take into…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Kelly O. Marshall , Omid Poursaeed , Sergiu Oprea , Amit Kumar , Anushrut Jignasu , Chinmay Hegde , Yilei Li , Rakesh Ranjan

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

Novel view synthesis from images, for example, with 3D Gaussian splatting, has made great progress. Rendering fidelity and speed are now ready even for demanding virtual reality applications. However, the problem of assisting humans in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Ayaka Yasunaga , Hideo Saito , Dieter Schmalstieg , Shohei Mori

Textured high-fidelity 3D models are crucial for games, AR/VR, and film, but human-aligned evaluation methods still fall behind despite recent advances in 3D reconstruction and generation. Existing metrics, such as Chamfer Distance, often…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Tianyu Luan , Xuelu Feng , Zixin Zhu , Phani Nuney , Sheng Liu , Xuan Gong , David Doermann , Chunming Qiao , Junsong Yuan

In this paper, we introduce \textit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for single-view scene reconstruction typically rely on object retrieval or the regression…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yuhan Ping , Yuan Liu , Xiaoxiao Long , Peng Wang , Junhui Hou , Jianyi Zheng , Jia Pan , Xin Li , Cheng Lin

This article aims to use graphic engines to simulate a large number of training data that have free annotations and possibly strongly resemble to real-world data. Between synthetic and real, a two-level domain gap exists, involving content…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yue Yao , Liang Zheng , Xiaodong Yang , Milind Napthade , Tom Gedeon

Diffusion models are advancing autonomous driving by enabling realistic data synthesis, predictive end-to-end planning, and closed-loop simulation, with a primary focus on temporally consistent generation. However, large-scale 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Yu Yang , Alan Liang , Jianbiao Mei , Yukai Ma , Yong Liu , Gim Hee Lee

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certain attributes within a generated image. Although successful,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Jonghyun Lee , Hansam Cho , Youngjoon Yoo , Seoung Bum Kim , Yonghyun Jeong

Indoor scene semantic parsing from RGB images is very challenging due to occlusions, object distortion, and viewpoint variations. Going beyond prior works that leverage geometry information, typically paired depth maps, we present a new…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Zhengzhe Liu , Xiaojuan Qi , Chi-Wing Fu

Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided image editing. While text guidance is an intuitive editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jooyoung Choi , Yunjey Choi , Yunji Kim , Junho Kim , Sungroh Yoon

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

We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

The accurate representation of 3D building models in urban environments is significantly hindered by challenges such as texture occlusion, blurring, and missing details, which are difficult to mitigate through standard photogrammetric…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Qisen Shang , Han Hu , Haojia Yu , Bo Xu , Libin Wang , Qing Zhu

Conditional image generation models have achieved remarkable results by leveraging text-based control to generate customized images. However, the high resource demands of these models and the scarcity of well-annotated data have hindered…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yicheng Jiang , Jin Yuan , Hua Yuan , Yao Zhang , Yong Rui