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Liang Li (李 亮)
Address: A201,55 Building, Jinnan Campus, Tianjin University, 135, Yaguan Rd, Jinnan Dist. Tianjin, 300350, China
Email: liangli at tju dot edu dot cn
Phone: +86-15822370924
I am an associate professor in College of Intelligence and Computing, Tianjin University, China. I received my PhD degree from Tianjin University in 2014 under supervision of Prof. Jiawan Zhang, and working closely with Prof. Wei Feng and Prof. Xiaojie Guo. My research lies in the areas of computer vision and machine learning, especially in the problems of object localization and degraded image restoration. View me on Google Scholar.
Academic Activities
Reviewer of CVPR 2022, International Conference on Pattern Recognition， Computer Science, NSF of China
Collabrators
Professor Jiawan Zhang
Professor Wei Feng
Professor Xiaojie Guo
Projects
2023.6-2024.12 "Development of general purpose distributed computing framework", China railway liuyuan Group Co. Ltd., PI (¥460,000)
2020.10-2023.10 "Enhancement of the content and quality of digital cultural heritage", National Key Research and Development Project， MOST of China, PI (¥180,000)
2022.06-2023.06 "Software development for rain and defrost and defogging image recognition", CATARC (Tianjin) Automotive Engineering Research Institute, PI (¥450,000)
2022.6-2023.6 "Survey on protection souce code from decompiling or inverse engineering", China railway liuyuan Group Co. Ltd., PI (¥60,000)
2017.01-2019.12 "Superpixel grid based generic object localization", NSF of China, PI (¥210,000)
2017.11-2019.11 "Object localization algorithm for images taken in bad weather conditions", Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, PI (¥50,000)

Genling Li, Liang Li*, Jiawan Zhang. Hierarchical Semantic Broadcasting Network for Real-time Semantic Segmentation. Signal Processing Letters. vol.29, 2022. [pdf]

Genling Li, Liang Li*, Jiawan Zhang. BiAttnNet: Bilateral Attention for Improving Real-time Semantic Segmentation. Signal Processing Letters. vol. 29, 2022. [pdf]

Xinhui Li, Liang Li, Xiaojie Guo. Synthetic-to-real Generalization for Semantic Segmentation. IEEE International Conference on Multimedia & Expo (ICME). 2022 [pdf]

Zhengzhang Hou, Liang Li, Xiaojie Guo. Feature-guided Blind Face Restoration with GAN Prior. IEEE International Conference on Multimedia & Expo (ICME). 2022 [pdf]

Dong Han, Liang Li,Xiaojie Guo and Jiayi Ma. Multi-exposure Image Fusion via Deep Perceptual Enhancement. Information Fusion. vol. 79, pp. 248-262, 2022 [pdf] [code]

Shangjie Ren, Xiongri Shen, Jingjiang Xu, Liang Li*, et al.. Imaging Depth Adaptive Resolution Enhancement for Optical Coherence Tomography via Deep Neural Network with External Attention. Physics in Medicine & Biology. vol. 66, pp. 1-13, 2021 [pdf]

Hailing Wang, Qiaoyu Tian, Liang Li and Xiaojie Guo. Image Demoiréing with a Dual-Domain Distilling Network. IEEE International Conference on Multimedia & Expo (ICME), Oral. 2021. [pdf]

Kai Wang, Liang Li*, Jiawan Zhang. End-to-end Trainable Network for Superpixel and Image Segmentation. Pattern Recognition Letters. vol. 40, pp. 135-142, 2020. [pdf]

Mubinun Awaisu, Liang Li* Junjie Peng, Jiawan Zhang. Fast Superpixel Segmentation with Deep Features. Computer Graphics International Conference (CGI). 2019. [pdf]

Jiachuan Sheng, Yaqi Chen, Yuzhi Li, Liang Li*. Embedded Learning for Computerized Production of Movie Trailers. Multimed Tools Appl,. 2018. [pdf]

Liang Li, Xiaojie Guo*, Wei Feng, Jiawan Zhang. Soft Clustering Guided Image Smoothing. IEEE International Conference on Multimedia & Expo(ICME). Accept as Oral, 2018. [pdf]

Xiaojie Guo, Liang Li*, Jiawan Zhang. Structure-Texture Decomposition Via Joint Structure Discovery and Texture Smoothing. IEEE International Conference on Multimedia & Expo(ICME). 2018. [pdf, project]

Yonghua Zhang, Liang Li, Runmin Cong, Xiaojie Guo, Hui Xu, Jiawan Zhang*. Co-saliency detection via hierachical consistency measure. IEEE International Conference on Multimedia & Expo(ICME). Accept as Oral, 2018. [pdf]

Liang Li, Wei Feng*, Jiawan Zhang. Contrast enhancement based single image dehazing via TV-L1 minimization. IEEE International Conference on Multimedia & Expo(ICME). 2014. [pdf]

Liang Li, Wei Feng*, Liang Wan, Jiawan Zhang. Maximum cohesive grid of superpixels for fast object localization. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2013. [pdf]

Jiawan Zhang, Yunkun Hao, Liang Li*, Di Sun, Li Yuan. Storywizard: A framework for fast stylized story illustration. The Visual Computer, 28(6-8):877-887. 2012. [pdf]

Jiawan Zhang, Liang Li*, Yi Zhang, Guoqiang Yang, Xiaochun Cao, Jizhou Sun. Video dehazing with spatial and temporal coherence. The Visual Computer, 27(6-8):749-757. 2011. [pdf]

Liang Li, Wei Feng, Jiawan Zhang*, Jianmin Jiang. Video motion estimation with temporal coherence. International Conference on Virtual Reality Continuum and Its Application in Industry (VRCAI). 2011. [pdf]

Jiawan Zhang, Liang Li, Yi Zhang, Guoqiang Yang. Local albedo-insensitive single image dehazing. The Visual Computer, 26(6-8):761-768. 2010. [pdf]

Jiawan Zhang, Liang Li, Liangfu Lv. A novel visulization approach for efficient network scans detection. International Conference on Security Technology. 2008. [pdf]

Under construction.
Digital Image Processing
Fall 2017
Syllabus: Image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices. Term project.

Introduction to Computer Vision
Spring 2018
This course is designed to give graduate students a comprehensive understanding of topics at the confluence of computer vision, computer graphics, machine learning and image processing. This module will expose students to the most recent research and highlight the foundations and trends in these fields. We will discuss selected papers on most recent research problems, with topics covering lighting, geometry, image processing, medical image analysis, recognition and machine learning.
Under construction.