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Generative models have advanced significantly in realistic image synthesis, with diffusion models excelling in quality and stability. Recent multi-view diffusion models improve 3D-aware street view generation, but they struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Ji Li , Zhiwei Li , Shihao Li , Zhenjiang Yu , Boyang Wang , Haiou Liu

Diffusion-based image generators can now produce high-quality and diverse samples, but their success has yet to fully translate to 3D generation: existing diffusion methods can either generate low-resolution but 3D consistent outputs, or…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Animesh Karnewar , Niloy J. Mitra , Andrea Vedaldi , David Novotny

Novel view synthesis from a single image has recently achieved remarkable results, although the requirement of some form of 3D, pose, or multi-view supervision at training time limits the deployment in real scenarios. This work aims at…

Computer Vision and Pattern Recognition · Computer Science 2021-12-16 Pierluigi Zama Ramirez , Diego Martin Arroyo , Alessio Tonioni , Federico Tombari

Image-conditioned generation methods, such as depth- and canny-conditioned approaches, have demonstrated remarkable abilities for precise image synthesis. However, existing models still struggle to accurately control the content of multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Dewei Zhou , Mingwei Li , Zongxin Yang , Yi Yang

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zi-Xin Zou , Weihao Cheng , Yan-Pei Cao , Shi-Sheng Huang , Ying Shan , Song-Hai Zhang

Existing works in single-image human reconstruction suffer from weak generalizability due to insufficient training data or 3D inconsistencies for a lack of comprehensive multi-view knowledge. In this paper, we introduce MagicMan, a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xu He , Xiaoyu Li , Di Kang , Jiangnan Ye , Chaopeng Zhang , Liyang Chen , Xiangjun Gao , Han Zhang , Zhiyong Wu , Haolin Zhuang

We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achieve this, we use a monocular depth estimator that transfers…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Yash Kant , Aliaksandr Siarohin , Michael Vasilkovsky , Riza Alp Guler , Jian Ren , Sergey Tulyakov , Igor Gilitschenski

Recent advancements in text-to-3D generation, building on the success of high-performance text-to-image generative models, have made it possible to create imaginative and richly textured 3D objects from textual descriptions. However, a key…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Dongseok Shim , Yichun Shi , Kejie Li , H. Jin Kim , Peng Wang

Generating multi-view human images from a single view is a complex and significant challenge. Although recent advancements in multi-view object generation have shown impressive results with diffusion models, novel view synthesis for humans…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yu Feng , Shunsi Zhang , Jian Shu , Hanfeng Zhao , Guoliang Pang , Chi Zhang , Hao Wang

Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand in stark contrast to the compact, structured, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuan Li , Cheng Lin , Yuan Liu , Xiaoxiao Long , Chenxu Zhang , Ningna Wang , Xin Li , Wenping Wang , Xiaohu Guo

While single-concept customization has been studied in 3D, multi-concept customization remains largely unexplored. To address this, we propose MultiDreamer3D that can generate coherent multi-concept 3D content in a divide-and-conquer…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Wooseok Song , Seunggyu Chang , Jaejun Yoo

Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Álvaro Barbero Jiménez

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

Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

We present MVD-Fusion: a method for single-view 3D inference via generative modeling of multi-view-consistent RGB-D images. While recent methods pursuing 3D inference advocate learning novel-view generative models, these generations are not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Hanzhe Hu , Zhizhuo Zhou , Varun Jampani , Shubham Tulsiani

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

Advancements in text-to-image diffusion models have led to significant progress in fast 3D content creation. One common approach is to generate a set of multi-view images of an object, and then reconstruct it into a 3D model. However, this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Yiftach Edelstein , Or Patashnik , Dana Cohen-Bar , Lihi Zelnik-Manor

Recent breakthroughs in video generation, powered by large-scale datasets and diffusion techniques, have shown that video diffusion models can function as implicit 4D novel view synthesizers. Nevertheless, current methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yihao Zhi , Chenghong Li , Hongjie Liao , Xihe Yang , Zhengwentai Sun , Jiahao Chang , Xiaodong Cun , Wensen Feng , Xiaoguang Han

We present iFusion, a novel 3D object reconstruction framework that requires only two views with unknown camera poses. While single-view reconstruction yields visually appealing results, it can deviate significantly from the actual object,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Chin-Hsuan Wu , Yen-Chun Chen , Bolivar Solarte , Lu Yuan , Min Sun

Recent advancements in 3D diffusion-based semantic scene generation have gained attention. However, existing methods rely on unconditional generation and require multiple resampling steps when editing scenes, which significantly limits…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Haowen Zheng , Yanyan Liang
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