no code implementations • 16 Aug 2020 • Xinyu Gong, Wuyang Chen, Yifan Jiang, Ye Yuan, Xian-Ming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
Such simplification limits the fusion of information at different scales and fails to maintain high-resolution representations.
no code implementations • 5 Aug 2020 • Wei Hu, Jiahao Pang, Xian-Ming Liu, Dong Tian, Chia-Wen Lin, Anthony Vetro
Geometric data acquired from real-world scenes, e. g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc.
no code implementations • 9 Jun 2020 • Bo Pang, Deming Zhai, Junjun Jiang, Xian-Ming Liu
Image enhancement from degradation of rainy artifacts plays a critical role in outdoor visual computing systems.
2 code implementations • 18 May 2020 • Junjun Jiang, He Sun, Xian-Ming Liu, Jiayi Ma
Recently, single gray/RGB image super-resolution reconstruction task has been extensively studied and made significant progress by leveraging the advanced machine learning techniques based on deep convolutional neural networks (DCNNs).
no code implementations • 17 Mar 2020 • Ruifeng Shi, Deming Zhai, Xian-Ming Liu, Junjun Jiang, Wen Gao
However, the performance of CNN-based classification approach depends on a large amount of high-quality manually labeled training data, which are inevitably introduced noise on labels in practice, leading to model overfitting and performance degradation.
no code implementations • 14 Mar 2020 • Qiang Li, Xian-Ming Liu, Kaige Han, Cheng Guo, Xiangyang Ji, Xiaolin Wu
Whole slide imaging (WSI) is an emerging technology for digital pathology.
no code implementations • 4 Mar 2020 • Yongsen Zhao, Deming Zhai, Junjun Jiang, Xian-Ming Liu
Hyperspectral image (HSI) denoising is of crucial importance for many subsequent applications, such as HSI classification and interpretation.
2 code implementations • ICLR 2020 • Wuyang Chen, Xinyu Gong, Xian-Ming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
We present FasterSeg, an automatically designed semantic segmentation network with not only state-of-the-art performance but also faster speed than current methods.
Ranked #1 on Semantic Segmentation on BDD
1 code implementation • 2 Aug 2019 • Tao Hu, Lichao Huang, Xian-Ming Liu, Han Shen
Our tracker achieves leading performance in OTB2013, OTB2015, VOT2015, VOT2016 and LaSOT, and operates at a real-time speed of 26 FPS, which indicates our method is effective and practical.
no code implementations • 5 Jul 2019 • Wenxiang Zuo, Qiang Li, Xian-Ming Liu
As a real scenes sensing approach, depth information obtains the widespread applications.
no code implementations • 11 Jun 2019 • Yuanchao Bai, Huizhu Jia, Ming Jiang, Xian-Ming Liu, Xiaodong Xie, Wen Gao
Blind image deblurring is a challenging problem in computer vision, which aims to restore both the blur kernel and the latent sharp image from only a blurry observation.
1 code implementation • 12 Sep 2018 • Junjun Jiang, Jiayi Ma, Zheng Wang, Chen Chen, Xian-Ming Liu
The key idea of RLPA is to exploit knowledge (e. g., the superpixel based spectral-spatial constraints) from the observed hyperspectral images and apply it to the process of label propagation.
1 code implementation • 6 Sep 2018 • Ding Liu, Bihan Wen, Jianbo Jiao, Xian-Ming Liu, Zhangyang Wang, Thomas S. Huang
Second we propose a deep neural network solution that cascades two modules for image denoising and various high-level tasks, respectively, and use the joint loss for updating only the denoising network via back-propagation.
no code implementations • 22 Feb 2018 • Yuanchao Bai, Gene Cheung, Xian-Ming Liu, Wen Gao
We leverage the new graph spectral interpretation for RGTV to design an efficient algorithm that solves for the skeleton image and the blur kernel alternately.
no code implementations • 24 Dec 2017 • Yuanchao Bai, Gene Cheung, Xian-Ming Liu, Wen Gao
The problem can be solved in two parts: i) estimate a blur kernel from the blurry image, and ii) given estimated blur kernel, de-convolve blurry input to restore the target image.
no code implementations • 15 Dec 2017 • Tobias G. Tiecke, Xian-Ming Liu, Amy Zhang, Andreas Gros, Nan Li, Gregory Yetman, Talip Kilic, Siobhan Murray, Brian Blankespoor, Espen B. Prydz, Hai-Anh H. Dang
Obtaining high accuracy in estimation of population distribution in rural areas remains a very challenging task due to the simultaneous requirements of sufficient sensitivity and resolution to detect very sparse populations through remote sensing as well as reliable performance at a global scale.
no code implementations • ICCV 2017 • Ding Liu, Zhaowen Wang, Yuchen Fan, Xian-Ming Liu, Zhangyang Wang, Shiyu Chang, Thomas Huang
Second, we reduce the complexity of motion between neighboring frames using a spatial alignment network that is much more robust and efficient than competing alignment methods and can be jointly trained with the temporal adaptive network in an end-to-end manner.
no code implementations • 27 Jul 2017 • Amy Zhang, Xian-Ming Liu, Andreas Gros, Tobias Tiecke
Our work is some of the first to create population density maps from building detection on a large scale.
no code implementations • ICCV 2015 • Chunshui Cao, Xian-Ming Liu, Yi Yang, Yinan Yu, Jiang Wang, Zilei Wang, Yongzhen Huang, Liang Wang, Chang Huang, Wei Xu, Deva Ramanan, Thomas S. Huang
While feedforward deep convolutional neural networks (CNNs) have been a great success in computer vision, it is important to remember that the human visual contex contains generally more feedback connections than foward connections.
no code implementations • CVPR 2015 • Xian-Ming Liu, Rongrong Ji, Changhu Wang, Wei Liu, Bineng Zhong, Thomas S. Huang
A hierarchical shape parsing strategy is proposed to partition and organize image components into a hierarchical structure in the scale space.