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In this paper, we consider the task of space-time video super-resolution (ST-VSR), namely, expanding a given source video to a higher frame rate and resolution simultaneously. However, most existing schemes either consider a fixed…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Yuantong Zhang , Daiqin Yang , Zhenzhong Chen , Wenpeng Ding

As super-resolution (SR) techniques introduce unique distortions that fundamentally differ from those caused by traditional degradation processes (e.g., compression), there is an increasing demand for specialized video quality assessment…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Yixiao Li , Xiaoyuan Yang , Weide Liu , Xin Jin , Xu Jia , Yukun Lai , Paul L Rosin , Haotao Liu , Wei Zhou

Video restoration (VR) aims to recover high-quality videos from degraded ones. Although recent zero-shot VR methods using pre-trained diffusion models (DMs) show good promise, they suffer from approximation errors during reverse diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Hengkang Wang , Yang Liu , Huidong Liu , Chien-Chih Wang , Yanhui Guo , Hongdong Li , Bryan Wang , Ju Sun

Video super-resolution (VSR) is the task of restoring high-resolution frames from a sequence of low-resolution inputs. Different from single image super-resolution, VSR can utilize frames' temporal information to reconstruct results with…

Image and Video Processing · Electrical Eng. & Systems 2022-08-25 Wenyi Lian , Wenjing Lian

The capability of video super-resolution (VSR) to synthesize high-resolution (HR) video from ideal datasets has been demonstrated in many works. However, applying the VSR model to real-world video with unknown and complex degradation…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Yexing Song , Meilin Wang , Zhijing Yang , Xiaoyu Xian , Yukai Shi

Recently, latent diffusion models has demonstrated promising performance in real-world video super-resolution (VSR) task, which can reconstruct high-quality videos from distorted low-resolution input through multiple diffusion steps.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Hanting Li , Huaao Tang , Jianhong Han , Tianxiong Zhou , Jiulong Cui , Haizhen Xie , Yan Chen , Jie Hu

As deep convolutional neural networks (DNNs) are widely used in various fields of computer vision, leveraging the overfitting ability of the DNN to achieve video resolution upscaling has become a new trend in the modern video delivery…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Gen Li , Jie Ji , Minghai Qin , Wei Niu , Bin Ren , Fatemeh Afghah , Linke Guo , Xiaolong Ma

Video super-resolution (VSR) and frame interpolation (FI) are traditional computer vision problems, and the performance have been improving by incorporating deep learning recently. In this paper, we investigate the problem of jointly…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Jaeyeon Kang , Younghyun Jo , Seoung Wug Oh , Peter Vajda , Seon Joo Kim

Video colorization is a challenging and highly ill-posed problem. Although recent years have witnessed remarkable progress in single image colorization, there is relatively less research effort on video colorization and existing methods…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Yihao Liu , Hengyuan Zhao , Kelvin C. K. Chan , Xintao Wang , Chen Change Loy , Yu Qiao , Chao Dong

Multi-view video reconstruction plays a vital role in computer vision, enabling applications in film production, virtual reality, and motion analysis. While recent advances such as 4D Gaussian Splatting (4DGS) have demonstrated impressive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Zhixin Xu , Hengyu Zhou , Yuan Liu , Wenhan Xue , Hao Pan , Wenping Wang , Bin Wang

Video Super-Resolution (VSR) aims to recover sequences of high-resolution (HR) frames from low-resolution (LR) frames. Previous methods mainly utilize temporally adjacent frames to assist the reconstruction of target frames. However, in the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Yongjie Chen , Tieru Wu

Image and video synthesis are closely related areas aiming at generating content from noise. While rapid progress has been demonstrated in improving image-based models to handle large resolutions, high-quality renderings, and wide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Yu Tian , Jian Ren , Menglei Chai , Kyle Olszewski , Xi Peng , Dimitris N. Metaxas , Sergey Tulyakov

3D super-resolution aims to reconstruct high-fidelity 3D models from low-resolution (LR) multi-view images. Early studies primarily focused on single-image super-resolution (SISR) models to upsample LR images into high-resolution images.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Hyun-kyu Ko , Dongheok Park , Youngin Park , Byeonghyeon Lee , Juhee Han , Eunbyung Park

In this paper, we explore the space-time video super-resolution task, which aims to generate a high-resolution (HR) slow-motion video from a low frame rate (LFR), low-resolution (LR) video. A simple solution is to split it into two…

Computer Vision and Pattern Recognition · Computer Science 2020-02-27 Xiaoyu Xiang , Yapeng Tian , Yulun Zhang , Yun Fu , Jan P. Allebach , Chenliang Xu

The popularity of high and ultra-high definition displays has led to the need for methods to improve the quality of videos already obtained at much lower resolutions. Current Video Super-Resolution methods are not robust to mismatch between…

Computer Vision and Pattern Recognition · Computer Science 2020-10-26 Santiago López-Tapia , Alice Lucas , Rafael Molina , Aggelos K. Katsaggelos

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generation models, demonstrate promising performance in generating…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yichen Ouyang , jianhao Yuan , Hao Zhao , Gaoang Wang , Bo zhao

The rapid advancement of diffusion-based video generation models has led to increasingly realistic synthetic content, presenting new challenges for video forgery detection. Existing methods often struggle to capture fine-grained temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Xi Xue , Kunio Suzuki , Nabarun Goswami , Takuya Shintate

Video super-resolution (VSR) can achieve better performance compared to single image super-resolution by additionally leveraging temporal information. In particular, the recurrent-based VSR model exploits long-range temporal information…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Xingyu Zhou , Wei Long , Jingbo Lu , Shiyin Jiang , Weiyi You , Haifeng Wu , Shuhang Gu

Masked-based autoregressive models have demonstrated promising image generation capability in continuous space. However, their potential for video generation remains under-explored. In this paper, we propose \textbf{VideoMAR}, a concise and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Hu Yu , Biao Gong , Hangjie Yuan , DanDan Zheng , Weilong Chai , Jingdong Chen , Kecheng Zheng , Feng Zhao

In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. We leverage an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Xin Li , Wenqing Chu , Ye Wu , Weihang Yuan , Fanglong Liu , Qi Zhang , Fu Li , Haocheng Feng , Errui Ding , Jingdong Wang