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Related papers: 3D Object Manipulation in a Single Image using Gen…

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Achieving precise, object-level control in image editing remains challenging: 2D methods lack 3D awareness and often yield ambiguous or implausible results, while existing 3D-aware approaches rely on heavy optimization or incomplete…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yuhuan Xie , Aoxuan Pan , Yi-Hua Huang , Chirui Chang , Peng Dai , Xin Yu , Xiaojuan Qi

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

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Object-level manipulation, relocating or reorienting objects in images or videos while preserving scene realism, is central to film post-production, AR, and creative editing. Yet existing methods struggle to jointly achieve three core…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Penghui Ruan , Bojia Zi , Xianbiao Qi , Youze Huang , Rong Xiao , Pichao Wang , Jiannong Cao , Yuhui Shi

Recent text-to-image generative models can generate high-fidelity images from text prompts. However, these models struggle to consistently generate the same objects in different contexts with the same appearance. Consistent object…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Alec Helbling , Evan Montoya , Duen Horng Chau

Model customization introduces new concepts to existing text-to-image models, enabling the generation of these new concepts/objects in novel contexts. However, such methods lack accurate camera view control with respect to the new object,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Nupur Kumari , Grace Su , Richard Zhang , Taesung Park , Eli Shechtman , Jun-Yan Zhu

Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently recovering geometry, but still cannot accurately model the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zekai Gu , Shuoxuan Feng , Yansong Wang , Hanzhuo Huang , Zhongshuo Du , Chengfeng Zhao , Chengwei Ren , Peng Wang , Yuan Liu

Precise geometric control in image generation is essential for engineering \& product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Phillip Mueller , Talip Uenlue , Sebastian Schmidt , Marcel Kollovieh , Jiajie Fan , Stephan Guennemann , Lars Mikelsons

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

We present Image Sculpting, a new framework for editing 2D images by incorporating tools from 3D geometry and graphics. This approach differs markedly from existing methods, which are confined to 2D spaces and typically rely on textual…

Graphics · Computer Science 2024-01-04 Jiraphon Yenphraphai , Xichen Pan , Sainan Liu , Daniele Panozzo , Saining Xie

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack precise control, and the associated methods typically specialize…

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiacheng Chen , Ramin Mehran , Xuhui Jia , Saining Xie , Sanghyun Woo

Text-to-image diffusion models have made significant progress in image generation, allowing for effortless customized generation. However, existing image editing methods still face certain limitations when dealing with personalized image…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Yuhong Zhang , Han Wang , Yiwen Wang , Rong Xie , Li Song

Despite significant advances in modeling image priors via diffusion models, 3D-aware image editing remains challenging, in part because the object is only specified via a single image. To tackle this challenge, we propose 3D-Fixup, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Yen-Chi Cheng , Krishna Kumar Singh , Jae Shin Yoon , Alex Schwing , Liangyan Gui , Matheus Gadelha , Paul Guerrero , Nanxuan Zhao

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

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generative power of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Giuseppe Vecchio , Renato Sortino , Simone Palazzo , Concetto Spampinato

Manipulating the illumination of a 3D scene within a single image represents a fundamental challenge in computer vision and graphics. This problem has traditionally been addressed using inverse rendering techniques, which involve explicit…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Shrisha Bharadwaj , Haiwen Feng , Giorgio Becherini , Victoria Fernandez Abrevaya , Michael J. Black

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

The success of image generative models has enabled us to build methods that can edit images based on text or other user input. However, these methods are bespoke, imprecise, require additional information, or are limited to only 2D image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Rahul Sajnani , Jeroen Vanbaar , Jie Min , Kapil Katyal , Srinath Sridhar
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