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This is a technical report on the 360-degree panoramic image generation task based on diffusion models. Unlike ordinary 2D images, 360-degree panoramic images capture the entire $360^\circ\times 180^\circ$ field of view. So the rightmost…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Mengyang Feng , Jinlin Liu , Miaomiao Cui , Xuansong Xie

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

Recent prosperity of text-to-image diffusion models, e.g. Stable Diffusion, has stimulated research to adapt them to 360-degree panorama generation. Prior work has demonstrated the feasibility of using conventional low-rank adaptation…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Jinhong Ni , Chang-Bin Zhang , Qiang Zhang , Jing Zhang

Text-driven 3D scene generation has seen significant advancements recently. However, most existing methods generate single-view images using generative models and then stitch them together in 3D space. This independent generation for each…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Wenrui Li , Fucheng Cai , Yapeng Mi , Zhe Yang , Wangmeng Zuo , Xingtao Wang , Xiaopeng Fan

The advent of text-driven 360-degree panorama generation, enabling the synthesis of 360-degree panoramic images directly from textual descriptions, marks a transformative advancement in immersive visual content creation. This innovation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Hai Wang , Xiaoyu Xiang , Weihao Xia , Jing-Hao Xue

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

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

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

Recent advances in image generation have led to remarkable improvements in synthesizing perspective images. However, these models still struggle with panoramic image generation due to unique challenges, including varying levels of geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Hakan Çapuk , Andrew Bond , Muhammed Burak Kızıl , Emir Göçen , Erkut Erdem , Aykut Erdem

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

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

In this paper, we propose a novel diffusion-based approach to generate stereo images given a text prompt. Since stereo image datasets with large baselines are scarce, training a diffusion model from scratch is not feasible. Therefore, we…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Aakash Garg , Libing Zeng , Andrii Tsarov , Nima Khademi Kalantari

Panorama video recently attracts more interest in both study and application, courtesy of its immersive experience. Due to the expensive cost of capturing 360-degree panoramic videos, generating desirable panorama videos by prompts is…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Qian Wang , Weiqi Li , Chong Mou , Xinhua Cheng , Jian Zhang

This paper introduces MVDiffusion, a simple yet effective method for generating consistent multi-view images from text prompts given pixel-to-pixel correspondences (e.g., perspective crops from a panorama or multi-view images given depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Shitao Tang , Fuyang Zhang , Jiacheng Chen , Peng Wang , Yasutaka Furukawa

Generating complete 360-degree panoramas from narrow field of view images is ongoing research as omnidirectional RGB data is not readily available. Existing GAN-based approaches face some barriers to achieving higher quality output, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Tianhao Wu , Chuanxia Zheng , Tat-Jen Cham

Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex structures and operations often pose challenges for non-experts to grasp. We present Diffusion…

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging for perspective video generators due to their limited field of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Ting-Hsuan Chen , Ying-Huan Chen , Tao Tu , Jie-Ying Lee , Cho-Ying Wu , Fangzhou Lin , Hengyuan Zhang , David Paz , Xinyu Huang , Yuliang Guo , Yu-Lun Liu , Yue Wang , Liu Ren

360$^\circ$ panoramas are extensively utilized as environmental light sources in computer graphics. However, capturing a 360$^\circ$ $\times$ 180$^\circ$ panorama poses challenges due to the necessity of specialized and costly equipment,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Jionghao Wang , Ziyu Chen , Jun Ling , Rong Xie , Li Song

Text-to-image diffusion models have recently attracted the interest of many researchers, and inverting the diffusion process can play an important role in better understanding the generative process and how to engineer prompts in order to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Florinel-Alin Croitoru , Vlad Hondru , Radu Tudor Ionescu , Mubarak Shah
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