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Related papers: MVDiffusion: Enabling Holistic Multi-view Image Ge…

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We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion model can achieve the generalizability of 2D diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Yichun Shi , Peng Wang , Jianglong Ye , Mai Long , Kejie Li , Xiao Yang

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Creating novel images by fusing visual cues from multiple sources is a fundamental yet underexplored problem in image-to-image generation, with broad applications in artistic creation, virtual reality and visual media. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zeren Xiong , Yue Yu , Zedong Zhang , Shuo Chen , Jian Yang , Jun Li

We introduce a novel method for generating 360{\deg} panoramas from text prompts or images. Our approach leverages recent advances in 3D generation by employing multi-view diffusion models to jointly synthesize the six faces of a cubemap.…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Nikolai Kalischek , Michael Oechsle , Fabian Manhardt , Philipp Henzler , Konrad Schindler , Federico Tombari

Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques, such as MultiDiffusion and SyncDiffusion, have further…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Stanislav Frolov , Brian B. Moser , Andreas Dengel

As a promising 3D generation technique, multiview diffusion (MVD) has received a lot of attention due to its advantages in terms of generalizability, quality, and efficiency. By finetuning pretrained large image diffusion models with 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Xin-Yang Zheng , Hao Pan , Yu-Xiao Guo , Xin Tong , Yang Liu

Diffusion models have recently gained recognition for generating diverse and high-quality content, especially in image synthesis. These models excel not only in creating fixed-size images but also in producing panoramic images. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiaoyu Zhang , Teng Zhou , Xinlong Zhang , Jia Wei , Yongchuan Tang

Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Emmanuelle Bourigault , Pauline Bourigault

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

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Transparent image layer generation plays a significant role in digital art and design workflows. Existing methods typically decompose transparent layers from a single RGB image using a set of tools or generate multiple transparent layers…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Dingbang Huang , Wenbo Li , Yifei Zhao , Xinyu Pan , Chun Wang , Yanhong Zeng , Bo Dai

We introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warped using metric depth and camera poses, significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Chenjie Cao , Chaohui Yu , Shang Liu , Fan Wang , Xiangyang Xue , Yanwei Fu

Diffusion models have emerged as effective tools for generating diverse and high-quality content. However, their capability in high-resolution image generation, particularly for panoramic images, still faces challenges such as visible seams…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Teng Zhou , Yongchuan Tang

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

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

Recent months have witnessed rapid progress in 3D generation based on diffusion models. Most advances require fine-tuning existing 2D Stable Diffsuions into multi-view settings or tedious distilling operations and hence fall short of 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Suyi Jiang , Haimin Luo , Haoran Jiang , Ziyu Wang , Jingyi Yu , Lan Xu

Multi-view image generation holds significant application value in computer vision, particularly in domains like 3D reconstruction, virtual reality, and augmented reality. Most existing methods, which rely on extending single images, face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Jiaqi Wu , Yaosen Chen , Shuyuan Zhu

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

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

Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha
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