Search Results for author: Chao Zhu

Found 7 papers, 1 papers with code

Learning To Restore Hazy Video: A New Real-World Dataset and a New Method

no code implementations CVPR 2021 Xinyi Zhang, Hang Dong, Jinshan Pan, Chao Zhu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Fei Wang

On the other hand, the video dehazing algorithms, which can acquire more satisfying dehazing results by exploiting the temporal redundancy from neighborhood hazy frames, receive less attention due to the absence of the video dehazing datasets.

Image Dehazing

Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection

no code implementations21 Oct 2020 Ye He, Chao Zhu, Xu-Cheng Yin

These two branches are trained in a mutual-supervised way with full body annotations and visible body annotations, respectively.

Occlusion Handling Pedestrian Detection

Stem-leaf segmentation and phenotypic trait extraction of maize shoots from three-dimensional point cloud

1 code implementation7 Sep 2020 Chao Zhu, Teng Miao, Tongyu Xu, Tao Yang, Na Li

However, automatic stem-leaf segmentation of maize shoots from three-dimensional (3D) point clouds remains challenging, especially for new emerging leaves that are very close and wrapped together during the seedling stage.

Machine learning driven synthesis of few-layered WTe2

no code implementations10 Oct 2019 Manzhang Xu, Bijun Tang, Yuhao Lu, Chao Zhu, Lu Zheng, Jingyu Zhang, Nannan Han, Yuxi Guo, Jun Di, Pin Song, Yongmin He, Lixing Kang, Zhiyong Zhang, Wu Zhao, Cuntai Guan, Xuewen Wang, Zheng Liu

Reducing the lateral scale of two-dimensional (2D) materials to one-dimensional (1D) has attracted substantial research interest not only to achieve competitive electronic device applications but also for the exploration of fundamental physical properties.

Semantic Bilinear Pooling for Fine-Grained Recognition

no code implementations3 Apr 2019 Xinjie Li, Chun Yang, Songlu Chen, Chao Zhu, Xu-Cheng Yin

Specifically, we design a generalized cross-entropy loss for the training of the proposed framework to fully exploit the semantic priors via considering the relevance between adjacent levels and enlarge the distance between samples of different coarse classes.

General Classification Multi-Label Learning

Design Flow of Accelerating Hybrid Extremely Low Bit-width Neural Network in Embedded FPGA

no code implementations31 Jul 2018 Junsong Wang, Qiuwen Lou, Xiaofan Zhang, Chao Zhu, Yonghua Lin, Deming Chen

To create such accelerators, we propose a design flow for accelerating the extremely low bit-width neural network (ELB-NN) in embedded FPGAs with hybrid quantization schemes.

Edge-computing Quantization

Cannot find the paper you are looking for? You can Submit a new open access paper.