no code implementations • 13 Jun 2023 • Mingchao Jiang, Yin Cheng, Linghai Liu
The development of online high-definition maps is significant since they provide real-time, accurate, and updatable geographic information for location-based applications, such as autonomous driving and intelligent transportation, thus improving the performance and reliability of these applications.
1 code implementation • 13 Apr 2023 • Wenbin Zou, Hongxia Gao, Liang Chen, Yunchen Zhang, Mingchao Jiang, Zhongxin Yu, Ming Tan
Stereo image super-resolution aims to improve the quality of high-resolution stereo image pairs by exploiting complementary information across views.
1 code implementation • 18 Nov 2021 • Tian Ye, Mingchao Jiang, Yunchen Zhang, Liang Chen, ErKang Chen, Pen Chen, Zhiyong Lu
However, due to the paradox caused by the variation of real captured haze and the fixed degradation parameters of the current networks, the generalization ability of recent dehazing methods on real-world hazy images is not ideal. To address the problem of modeling real-world haze degradation, we propose to solve this problem by perceiving and modeling density for uneven haze distribution.
Ranked #5 on Image Dehazing on Haze4k
1 code implementation • 12 Oct 2021 • Wenbin Zou, Mingchao Jiang, Yunchen Zhang, Liang Chen, Zhiyong Lu, Yi Wu
On this basis, we reduce the number of up-sampling and down-sampling and design a simple network structure.
Ranked #1 on Image Deblurring on RealBlur-R(trained on GoPro)
1 code implementation • 22 Apr 2021 • Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin
The promise of Deep Neural Network (DNN) powered Internet of Thing (IoT) devices has motivated a tremendous demand for automated solutions to enable fast development and deployment of efficient (1) DNNs equipped with instantaneous accuracy-efficiency trade-off capability to accommodate the time-varying resources at IoT devices and (2) dataflows to optimize DNNs' execution efficiency on different devices.
1 code implementation • ICCV 2021 • Arkabandhu Chowdhury, Mingchao Jiang, Swarat Chaudhuri, Chris Jermaine
Recent papers have suggested that transfer learning can outperform sophisticated meta-learning methods for few-shot image classification.