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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

Panoramic video generation enables immersive 360{\deg} content creation, valuable in applications that demand scene-consistent world exploration. However, existing panoramic video generation models struggle to leverage pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Yifei Xia , Shuchen Weng , Siqi Yang , Jingqi Liu , Chengxuan Zhu , Minggui Teng , Zijian Jia , Han Jiang , Boxin Shi

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

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

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

360{\deg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a more complete perspective of our surroundings. While…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Rundong Luo , Matthew Wallingford , Ali Farhadi , Noah Snavely , Wei-Chiu Ma

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…

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

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

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

Diffusion-based text-to-video generation (T2V) or image-to-video (I2V) generation have emerged as a prominent research focus. However, there exists a challenge in integrating the two generative paradigms into a unified model. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xinyu Xiao , Binbin Yang , Tingtian Li , Yipeng Yu , Sen Lei

Generative models, e.g., Stable Diffusion, have enabled the creation of photorealistic images from text prompts. Yet, the generation of 360-degree panorama images from text remains a challenge, particularly due to the dearth of paired…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Cheng Zhang , Qianyi Wu , Camilo Cruz Gambardella , Xiaoshui Huang , Dinh Phung , Wanli Ouyang , Jianfei Cai

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

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

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

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source models available for researchers and engineers. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Haoxin Chen , Menghan Xia , Yingqing He , Yong Zhang , Xiaodong Cun , Shaoshu Yang , Jinbo Xing , Yaofang Liu , Qifeng Chen , Xintao Wang , Chao Weng , Ying Shan

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

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

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
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