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Recent advances in text-to-image (T2I) diffusion models have enabled impressive image generation capabilities guided by text prompts. However, extending these techniques to video generation remains challenging, with existing text-to-video…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Weifeng Chen , Yatai Ji , Jie Wu , Hefeng Wu , Pan Xie , Jiashi Li , Xin Xia , Xuefeng Xiao , Liang Lin

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

Recent Text-to-Video (T2V) models have demonstrated powerful capability in visual simulation of real-world geometry and physical laws, indicating its potential as implicit world models. Inspired by this, we explore the feasibility of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yu Li , Menghan Xia , Gongye Liu , Jianhong Bai , Xintao Wang , Conglang Zhang , Yuxuan Lin , Ruihang Chu , Pengfei Wan , Yujiu Yang

The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an increasing demand for the creation of high-quality, immersive, and dynamic environments. However, existing generative techniques either focus solely on…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Renjie Li , Panwang Pan , Bangbang Yang , Dejia Xu , Shijie Zhou , Xuanyang Zhang , Zeming Li , Achuta Kadambi , Zhangyang Wang , Zhengzhong Tu , Zhiwen Fan

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

Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporally coherent video. Compared with broader video generation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Xianlong Wang , Wenbo Pan , Shijia Zhou , Ke Li , Yuqi Wang , Zeyu Ye , Hangtao Zhang , Leo Yu Zhang , Xiaohua Jia

The rapid advancement of diffusion models holds the promise of revolutionizing the application of VR and AR technologies, which typically require scene-level 4D assets for user experience. Nonetheless, existing diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Haiyang Zhou , Wangbo Yu , Jiawen Guan , Xinhua Cheng , Yonghong Tian , Li Yuan

Lifting perspective images and videos to 360{\deg} panoramas enables immersive 3D world generation. Existing approaches often rely on explicit geometric alignment between the perspective and the equirectangular projection (ERP) space. Yet,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Ziyi Wu , Daniel Watson , Andrea Tagliasacchi , David J. Fleet , Marcus A. Brubaker , Saurabh Saxena

Novel view synthesis (NVS) from a single image is highly ill-posed due to large unobserved regions, especially for views that deviate significantly from the input. While existing methods focus on consistency between the source and generated…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Xueyang Kang , Zhengkang Xiang , Zezheng Zhang , Kourosh Khoshelham

Text-driven Image to Video Generation (TI2V) aims to generate controllable video given the first frame and corresponding textual description. The primary challenges of this task lie in two parts: (i) how to identify the target objects and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xingrui Wang , Xin Li , Yaosi Hu , Hanxin Zhu , Chen Hou , Cuiling Lan , Zhibo Chen

We present a novel approach for generating 360-degree high-quality, spatio-temporally coherent human videos from a single image. Our framework combines the strengths of diffusion transformers for capturing global correlations across…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Ruizhi Shao , Youxin Pang , Zerong Zheng , Jingxiang Sun , Yebin Liu

Generating 3D scenes is still a challenging task due to the lack of readily available scene data. Most existing methods only produce partial scenes and provide limited navigational freedom. We introduce a practical and scalable solution…

Graphics · Computer Science 2025-09-26 Zhaoyang Zhang , Yannick Hold-Geoffroy , Miloš Hašan , Ziwen Chen , Fujun Luan , Julie Dorsey , Yiwei Hu

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

Generating high-quality 360{\deg} panoramic videos remains a significant challenge due to the fundamental differences between panoramic and traditional perspective-view projections. While perspective videos rely on a single viewpoint with a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Zeyu Dong , Yuyang Yin , Yuqi Li , Eric Li , Hao-Xiang Guo , Yikai Wang

$360^\circ$ videos offer a hyper-immersive experience that allows the viewers to explore a dynamic scene from full 360 degrees. To achieve more user-friendly and personalized content creation in $360^\circ$ video format, we seek to lift…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Jing Tan , Shuai Yang , Tong Wu , Jingwen He , Yuwei Guo , Ziwei Liu , Dahua Lin

While instruction-based image editing is emerging, extending it to 360$^\circ$ panoramas introduces additional challenges. Existing methods often produce implausible results in both equirectangular projections (ERP) and perspective views.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Haoyi Zhong , Fang-Lue Zhang , Andrew Chalmers , Taehyun Rhee

The emergence of Diffusion Transformers (DiT) has brought significant advancements to video generation, especially in text-to-video and image-to-video tasks. Although video generation is widely applied in various fields, most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Sen Liang , Zhentao Yu , Zhengguang Zhou , Teng Hu , Hongmei Wang , Yi Chen , Qin Lin , Yuan Zhou , Xin Li , Qinglin Lu , Zhibo Chen

Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle to accurately generate complex motion dynamics, leading to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Haoran Cheng , Liang Peng , Linxuan Xia , Yuepeng Hu , Hengjia Li , Qinglin Lu , Xiaofei He , Boxi Wu

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires the controllability of both subjects and motions. To that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yujie Wei , Shiwei Zhang , Zhiwu Qing , Hangjie Yuan , Zhiheng Liu , Yu Liu , Yingya Zhang , Jingren Zhou , Hongming Shan