English
Related papers

Related papers: RoomPainter: View-Integrated Diffusion for Consist…

200 papers

We present ZeroComp, an effective zero-shot 3D object compositing approach that does not require paired composite-scene images during training. Our method leverages ControlNet to condition from intrinsic images and combines it with a Stable…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Zitian Zhang , Frédéric Fortier-Chouinard , Mathieu Garon , Anand Bhattad , Jean-François Lalonde

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 TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Diffusion models currently achieve state-of-the-art performance for both conditional and unconditional image generation. However, so far, image diffusion models do not support tasks required for 3D understanding, such as view-consistent 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Zexiang Xu , Matthew Fisher , Paul Henderson , Hakan Bilen , Niloy J. Mitra , Paul Guerrero

Diffusion models have emerged as highly effective techniques for inpainting, however, they remain constrained by slow sampling rates. While recent advances have enhanced generation quality, they have also increased sampling time, thereby…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Tsiry Mayet , Pourya Shamsolmoali , Simon Bernard , Eric Granger , Romain Hérault , Clement Chatelain

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi

Have you ever thought that you can be an intelligent painter? This means that you can paint a picture with a few expected objects in mind, or with a desirable scene. This is different from normal inpainting approaches for which the location…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Wing-Fung Ku , Wan-Chi Siu , Xi Cheng , H. Anthony Chan

Subject-driven image inpainting has recently gained prominence in image editing with the rapid advancement of diffusion models. Beyond image guidance, recent studies have explored incorporating text guidance to achieve identity-preserved…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yicheng Yang , Pengxiang Li , Lu Zhang , Liqian Ma , Ping Hu , Siyu Du , Yunzhi Zhuge , Xu Jia , Huchuan Lu

Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in personalized text-to-image applications, particularly in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xierui Wang , Siming Fu , Qihan Huang , Wanggui He , Hao Jiang

Given a 3D mesh with a UV parameterization, we introduce a novel approach to generating textures from text prompts. While prior work uses optimization from Text-to-Image Diffusion models to generate textures and geometry, this is slow and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Julian Knodt , Xifeng Gao

We propose a zero-shot method for generating images in arbitrary spaces (e.g., a sphere for 360{\deg} panoramas and a mesh surface for texture) using a pretrained image diffusion model. The zero-shot generation of various visual content…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Kyeongmin Yeo , Jaihoon Kim , Minhyuk Sung

We present a novel method for 3D scene editing using diffusion models, designed to ensure view consistency and realism across perspectives. Our approach leverages attention features extracted from a single reference image to define the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Eyal Gomel , Lior Wolf

Video outpainting extends a video beyond its original boundaries by synthesizing missing border content. Compared with image outpainting, it requires not only per-frame spatial plausibility but also long-range temporal coherence, especially…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yueming Pan , Ruoyu Feng , Jianmin Bao , Chong Luo , Nanning Zheng

In this paper, part of the DREAMING Challenge - Diminished Reality for Emerging Applications in Medicine through Inpainting, we introduce a refined video inpainting technique optimised from the ProPainter method to meet the specialised…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Pengze Li , Lihao Liu , Carola-Bibiane Schönlieb , Angelica I Aviles-Rivero

Diffusion-based text-to-image generation models have significantly advanced the field of art content synthesis. However, current portrait stylization methods generally require either model fine-tuning based on examples or the employment of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Jin Liu , Huaibo Huang , Jie Cao , Ran He

Image inpaiting is an important task in image processing and vision. In this paper, we develop a general method for patch-based image inpainting by synthesizing new textures from existing one. A novel framework is introduced to find several…

Computer Vision and Pattern Recognition · Computer Science 2016-05-06 Tao Zhou , Brian Johnson , Rui Li

Multi-view generation with camera pose control and prompt-based customization are both essential elements for achieving controllable generative models. However, existing multi-view generation models do not support customization with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Minjung Shin , Hyunin Cho , Sooyeon Go , Jin-Hwa Kim , Youngjung Uh

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , Liefeng Bo

Recent progress in text-guided image inpainting, based on the unprecedented success of text-to-image diffusion models, has led to exceptionally realistic and visually plausible results. However, there is still significant potential for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Hayk Manukyan , Andranik Sargsyan , Barsegh Atanyan , Zhangyang Wang , Shant Navasardyan , Humphrey Shi