no code implementations • ECCV 2020 • Zhetong Liang, Shi Guo, Hong Gu, Huaqi Zhang, Lei Zhang
On one hand, most of the models are trained on video sequences with synthetic noise.
no code implementations • 20 Jan 2025 • Zixuan Chen, Yujin Wang, Xin Cai, Zhiyuan You, Zheming Lu, Fan Zhang, Shi Guo, Tianfan Xue
In this work, we propose UltraFusion, the first exposure fusion technique that can merge input with 9 stops differences.
no code implementations • 19 Dec 2024 • Shi Guo, Zixuan Chen, Ziran Zhang, Yutian Chen, Gangwei Xu, Tianfan Xue
High dynamic range (HDR) imaging is a crucial task in computational photography, which captures details across diverse lighting conditions.
no code implementations • 12 Jun 2024 • Ziran Zhang, Yongrui Ma, Yueting Chen, Feng Zhang, Jinwei Gu, Tianfan Xue, Shi Guo
This approach utilizes the internal statistics of a sequence to handle degraded event data under low-light conditions, improving the generalizability to different lighting and camera settings.
1 code implementation • 19 Feb 2024 • Yutian Chen, Shi Guo, Fangzheng Yu, Feng Zhang, Jinwei Gu, Tianfan Xue
In this work, we propose a dual-camera system consisting of an event camera and a conventional RGB camera for video motion magnification, providing temporally-dense information from the event stream and spatially-dense data from the RGB images.
1 code implementation • 25 Dec 2023 • Shi Guo, jianqi ma, Xi Yang, Zhengqiang Zhang, Lei Zhang
Extensive experiments demonstrate the leading VJDD performance of our method in term of restoration accuracy, perceptual quality and temporal consistency.
1 code implementation • 15 Dec 2023 • Zhengqiang Zhang, Ruihuang Li, Shi Guo, Yang Cao, Lei Zhang
Online video super-resolution (online-VSR) highly relies on an effective alignment module to aggregate temporal information, while the strict latency requirement makes accurate and efficient alignment very challenging.
no code implementations • 27 Feb 2023 • Shi Guo, Hongwei Yong, Xindong Zhang, jianqi ma, Lei Zhang
In this paper, we propose the spatial-frequency attention network (SFANet) to enhance the network's ability in exploiting long-range dependency.
1 code implementation • CVPR 2022 • Shi Guo, Xi Yang, jianqi ma, Gaofeng Ren, Lei Zhang
Denoising and demosaicking are two essential steps to reconstruct a clean full-color image from the raw data.
1 code implementation • 13 Mar 2022 • Xindong Zhang, Hui Zeng, Shi Guo, Lei Zhang
A highly efficient long-range attention block (ELAB) is then built by simply cascading two shift-conv with a GMSA module, which is further accelerated by using a shared attention mechanism.
Ranked #15 on
Image Super-Resolution
on Manga109 - 4x upscaling
1 code implementation • 15 Dec 2021 • Wenyu Liu, Gaofeng Ren, Runsheng Yu, Shi Guo, Jianke Zhu, Lei Zhang
Though deep learning-based object detection methods have achieved promising results on the conventional datasets, it is still challenging to locate objects from the low-quality images captured in adverse weather conditions.
2 code implementations • 29 Jun 2021 • jianqi ma, Shi Guo, Lei Zhang
Our experiments on the benchmark TextZoom dataset show that TPGSR can not only effectively improve the visual quality of scene text images, but also significantly improve the text recognition accuracy over existing STISR methods.
1 code implementation • ICCV 2021 • GuanYing Chen, Chaofeng Chen, Shi Guo, Zhetong Liang, Kwan-Yee K. Wong, Lei Zhang
Secondly, we conduct more sophisticated alignment and temporal fusion in the feature space of the coarse HDR video to produce better reconstruction.
1 code implementation • 25 Jan 2021 • Shi Guo, Zhetong Liang, Lei Zhang
Considering the fact that the green channel has twice the sampling rate and better quality than the red and blue channels in CFA raw data, we propose to use this green channel prior (GCP) to build a GCP-Net for the JDD-B task.
3 code implementations • CVPR 2019 • Shi Guo, Zifei Yan, Kai Zhang, WangMeng Zuo, Lei Zhang
While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on real-world noisy photographs.
Ranked #4 on
Denoising
on Darmstadt Noise Dataset
no code implementations • CVPR 2017 • Shuhang Gu, WangMeng Zuo, Shi Guo, Yunjin Chen, Chongyu Chen, Lei Zhang
To address these limitations, we propose a weighted analysis representation model for guided depth image enhancement, which advances the conventional methods in two aspects: (i) task driven learning and (ii) dynamic guidance.