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To watch 360{\deg} videos on normal 2D displays, we need to project the selected part of the 360{\deg} image onto the 2D display plane. In this paper, we propose a fully-automated framework for generating content-aware 2D normal-view…

Graphics · Computer Science 2017-09-12 Yeong Won Kim , Dae-Yong Jo , Chang-Ryeol Lee , Hyeok-Jae Choi , Yong Hoon Kwon , Kuk-Jin Yoon

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Generating high-quality videos that synthesize desired realistic content is a challenging task due to their intricate high-dimensionality and complexity of videos. Several recent diffusion-based methods have shown comparable performance by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Kihong Kim , Haneol Lee , Jihye Park , Seyeon Kim , Kwanghee Lee , Seungryong Kim , Jaejun Yoo

This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

Panoramic video generation has attracted growing attention due to its applications in virtual reality and immersive media. However, existing methods lack explicit motion control and struggle to generate scenes with large and complex…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Cheng Zhang , Hanwen Liang , Donny Y. Chen , Qianyi Wu , Konstantinos N. Plataniotis , Camilo Cruz Gambardella , Jianfei Cai

Video diffusion models provide powerful real-world simulators for embodied AI but remain limited in controllability for robotic manipulation. Recent works on trajectory-conditioned video generation address this gap but often rely on 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Yang Bai , Liudi Yang , George Eskandar , Fengyi Shen , Mohammad Altillawi , Ziyuan Liu , Gitta Kutyniok

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

Diffusion-based text-to-video generation has witnessed impressive progress in the past year yet still falls behind text-to-image generation. One of the key reasons is the limited scale of publicly available data (e.g., 10M video-text pairs…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Xiang Wang , Shiwei Zhang , Hangjie Yuan , Zhiwu Qing , Biao Gong , Yingya Zhang , Yujun Shen , Changxin Gao , Nong Sang

Recent advances in diffusion models have revolutionized video generation, offering superior temporal consistency and visual quality compared to traditional generative adversarial networks-based approaches. While this emerging field shows…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Yimu Wang , Xuye Liu , Wei Pang , Li Ma , Shuai Yuan , Paul Debevec , Ning Yu

Omnidirectional (360-degree) video is rapidly gaining popularity due to advancements in immersive technologies like virtual reality (VR) and extended reality (XR). However, real-time streaming of such videos, especially in live mobile…

Conditional diffusion models have exhibited superior performance in high-fidelity text-guided visual generation and editing. Nevertheless, prevailing text-guided visual diffusion models primarily focus on incorporating text-visual…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Zhilong Zhang , Zhaochen Yu , Jingwei Liu , Minkai Xu , Stefano Ermon , Bin Cui

Current diffusion-based text-to-video methods are limited to producing short video clips of a single shot and lack the capability to generate multi-shot videos with discrete transitions where the same character performs distinct activities…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Ozgur Kara , Krishna Kumar Singh , Feng Liu , Duygu Ceylan , James M. Rehg , Tobias Hinz

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

Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the score distillation sampling (SDS) loss, to bypass the data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yu-Jie Yuan , Leif Kobbelt , Jiwen Liu , Yuan Zhang , Pengfei Wan , Yu-Kun Lai , Lin Gao

Recent works have successfully extended large-scale text-to-image models to the video domain, producing promising results but at a high computational cost and requiring a large amount of video data. In this work, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Bo Peng , Xinyuan Chen , Yaohui Wang , Chaochao Lu , Yu Qiao

Digital human avatars aim to simulate the dynamic appearance of humans in virtual environments, enabling immersive experiences across gaming, film, virtual reality, and more. However, the conventional process for creating and animating…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Felix Taubner , Ruihang Zhang , Mathieu Tuli , Sherwin Bahmani , David B. Lindell

Generating a complete and explorable 360-degree visual world enables a wide range of downstream applications. While prior works have advanced the field, they remain constrained by either narrow field-of-view limitations, which hinder the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Yuyang Yin , HaoXiang Guo , Fangfu Liu , Mengyu Wang , Hanwen Liang , Eric Li , Yikai Wang , Xiaojie Jin , Yao Zhao , Yunchao Wei

World models, which predict future transitions from past observation and action sequences, have shown great promise for improving data efficiency in sequential decision-making. However, existing world models often require extensive…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Siqiao Huang , Jialong Wu , Qixing Zhou , Shangchen Miao , Mingsheng Long

Document dewarping aims to rectify deformations in photographic document images, thus improving text readability, which has attracted much attention and made great progress, but it is still challenging to preserve document structures. Given…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Weiguang Zhang , Huangcheng Lu , Maizhen Ning , Xiaowei Huang , Wei Wang , Kaizhu Huang , Qiufeng Wang

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi
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