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Despite the great success of large-scale text-to-image diffusion models in image generation and image editing, existing methods still struggle to edit the layout of real images. Although a few works have been proposed to tackle this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Tao Xia , Yudi Zhang , Ting Liu Lei Zhang

Neural Radiance Fields and 3D Gaussian Splatting have revolutionized 3D reconstruction and novel-view synthesis task. However, achieving photorealistic rendering from extreme novel viewpoints remains challenging, as artifacts persist across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jay Zhangjie Wu , Yuxuan Zhang , Haithem Turki , Xuanchi Ren , Jun Gao , Mike Zheng Shou , Sanja Fidler , Zan Gojcic , Huan Ling

We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ahmet Burak Yildirim , Mustafa Utku Aydogdu , Duygu Ceylan , Aysegul Dundar

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

Generating high-quality novel views of a scene from a single image requires maintaining structural coherence across different views, referred to as view consistency. While diffusion models have driven advancements in novel view synthesis,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiwoo Park , Tae Eun Choi , Youngjun Jun , Seong Jae Hwang

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

Controllable 3D style transfer seeks to restyle a 3D asset so that its textures match a reference image while preserving the integrity and multi-view consistency. The prevalent methods either rely on direct reference style token injection…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yuteng Ye , Zheng Zhang , Qinchuan Zhang , Di Wang , Youjia Zhang , Wenxiao Zhang , Wei Yang , Yuan Liu

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-observed areas. Methods that leverage generative priors to correct artifacts in these areas…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Riccardo de Lutio , Tobias Fischer , Yen-Yu Chang , Yuxuan Zhang , Jay Zhangjie Wu , Xuanchi Ren , Tianchang Shen , Katarina Tothova , Zan Gojcic , Haithem Turki

Generating realistic 3D scenes is an area of growing interest in computer vision and robotics. However, creating high-quality, diverse synthetic 3D content often requires expert intervention, making it costly and complex. Recently, efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Siyi Hu , Diego Martin Arroyo , Stephanie Debats , Fabian Manhardt , Luca Carlone , Federico Tombari

We present BetterScene, an approach to enhance novel view synthesis (NVS) quality for diverse real-world scenes using extremely sparse, unconstrained photos. BetterScene leverages the production-ready Stable Video Diffusion (SVD) model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Yuci Han , Charles Toth , John E. Anderson , William J. Shuart , Alper Yilmaz

Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Wenhao Chai , Xun Guo , Gaoang Wang , Yan Lu

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang

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

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

Current 3D Gaussian Splatting stylization approaches are limited in their ability to represent diverse artistic styles, frequently defaulting to low-level texture replacement or yielding semantically inconsistent outputs. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Cailin Zhuang , Yaoqi Hu , Xuanyang Zhang , Wei Cheng , Jiacheng Bao , Shengqi Liu , Yiying Yang , Xianfang Zeng , Gang Yu , Ming Li

Generative priors of large-scale text-to-image diffusion models enable a wide range of new generation and editing applications on diverse visual modalities. However, when adapting these priors to complex visual modalities, often represented…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Subin Kim , Kyungmin Lee , June Suk Choi , Jongheon Jeong , Kihyuk Sohn , Jinwoo Shin