no code implementations • 27 Dec 2024 • Keke Zhang, Weiling Chen, Tiesong Zhao, Zhou Wang
Image Quality Assessment (IQA) with references plays an important role in optimizing and evaluating computer vision tasks.
1 code implementation • 23 May 2024 • Zuoyong Li, Qinghua Lin, Haoyi Fan, Tiesong Zhao, David Zhang
In this paper, we propose a new semi-supervised learning method called SIAVC for industrial accident video classification.
no code implementations • 2 Mar 2024 • Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin
Thereby, we obtain an image free of low light and light effects, which improves the performance of nighttime object detection.
no code implementations • 8 Aug 2023 • Yiwen Xu, Dengfeng Liu, Liangtao Huang, Zhiquan Lin, Tiesong Zhao, Sam Kwong
In this paper, we employ the popular computer vision techniques of AI to design a non-invasive load monitoring method for smart electric energy management.
no code implementations • 7 Mar 2023 • Hongan Wei, Jiaqi Liu, Bo Chen, Liqun Lin, Weiling Chen, Tiesong Zhao
Second, we extend our 2D-JND model to SJND by jointly exploiting latitude projection and field of view during 360$^\circ$ display.
no code implementations • 3 Jan 2023 • Liqun Lin, Yang Zheng, Weiling Chen, Chengdong Lan, Tiesong Zhao
In this paper, we investigate the influence of four spatial PEAs (i. e. blurring, blocking, bleeding, and ringing) and two temporal PEAs (i. e. flickering and floating) on video quality.
1 code implementation • 10 Oct 2022 • Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen, Tiesong Zhao
Secondly, we design a Mask Query Transformer (MQFormer) to remove snow with the coarse mask, where we use two parallel encoders and a hybrid decoder to learn extensive snow features under lightweight requirements.
Ranked #2 on
Snow Removal
on SRRS
no code implementations • 19 May 2022 • Yannan Zheng, Weiling Chen, Rongfu Lin, Tiesong Zhao
In addition, we have also established a large-scale UIE database with subjective scores, namely Underwater Image Enhancement Database (UIED), which is utilized as a benchmark to compare all objective metrics.
no code implementations • 7 May 2022 • Liqun Lin, Zheng Wang, Jiachen He, Weiling Chen, Yiwen Xu, Tiesong Zhao
In this work, a semi-automatic labeling method is adopted to build a large-scale compressed video quality database, which allows us to label a large number of compressed videos with manageable human workload.
no code implementations • 7 May 2022 • Chengdong Lan, Hao Yan, Cheng Luo, Tiesong Zhao
At the decoder side, we combine the SI and adjacent viewpoints to reconstruct intermediate views using the GAN generator.
no code implementations • 7 May 2022 • Keke Zhang, Tiesong Zhao, Weiling Chen, Yuzhen Niu, Jinsong Hu
By combining the quality scores and their weights, we propose a unified SPQE metric for SR-IQA.
no code implementations • 7 May 2022 • Weiling Chen, Rongfu Lin, Honggang Liao, Tiesong Zhao, Ke Gu, Patrick Le Callet
Based on this task, we build an Underwater Image Utility Database (UIUD) and a learning-based Underwater Image Utility Measure (UIUM).
no code implementations • 7 May 2022 • Tiesong Zhao, Yuhang Huang, Weize Feng, Yiwen Xu, Sam Kwong
The ever-growing multimedia traffic has underscored the importance of effective multimedia codecs.
no code implementations • 29 Nov 2021 • Tiesong Zhao, Weize Feng, Hongji Zeng, Yuzhen Niu, Jiaying Liu
Second, we reuse the DPEG network in both motion compensation and quality enhancement modules, which are further combined with other necessary modules to formulate our JCEVC framework.
no code implementations • 29 Jun 2021 • Chao Zeng, Tiesong Zhao, Sam Kwong
Motivated by the auto-encoder mechanism and contrastive representation learning advances, we propose a learning-based metric for image captioning, which we call Intrinsic Image Captioning Evaluation($I^2CE$).
no code implementations • 16 Dec 2020 • Tiesong Zhao, YuTing Lin, Yiwen Xu, Weiling Chen, Zhou Wang
Image Super-Resolution (SR) techniques improve visual quality by enhancing the spatial resolution of images.
no code implementations • 1 Mar 2019 • Liqun Lin, Shiqi Yu, Tiesong Zhao, Member, Zhou Wang, Fellow, IEEE
To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs.