Search Results for author: Zehua Sheng

Found 7 papers, 5 papers with code

FocusNet: Classifying Better by Focusing on Confusing Classes

2 code implementations14 Oct 2021 Xue Zhang, Zehua Sheng, Hui-Liang Shen

We also introduce a novel focus-picking loss function to improve classification accuracy by encouraging FocusNet to focus on the most confusing classes.

Classification Image Classification +1

Iterative Deep Homography Estimation

1 code implementation CVPR 2022 Si-Yuan Cao, Jianxin Hu, Zehua Sheng, Hui-Liang Shen

On a variety of datasets, the 2-scale IHN outperforms all competitors by a large gap.

Homography Estimation

Structure Aggregation for Cross-Spectral Stereo Image Guided Denoising

1 code implementation CVPR 2023 Zehua Sheng, Zhu Yu, Xiongwei Liu, Si-Yuan Cao, Yuqi Liu, Hui-Liang Shen, Huaqi Zhang

Instead of aligning the input images via conventional stereo matching, we aggregate structures from the guidance image to estimate a clean structure map for the noisy target image, which is then used to regress the final denoising result with a spatially variant linear representation model.

Deblurring Denoising +2

Recurrent Homography Estimation Using Homography-Guided Image Warping and Focus Transformer

1 code implementation CVPR 2023 Si-Yuan Cao, Runmin Zhang, Lun Luo, Beinan Yu, Zehua Sheng, Junwei Li, Hui-Liang Shen

We propose the Recurrent homography estimation framework using Homography-guided image Warping and Focus transformer (FocusFormer), named RHWF.

Homography Estimation

Aggregating Feature Point Cloud for Depth Completion

no code implementations ICCV 2023 Zhu Yu, Zehua Sheng, Zili Zhou, Lun Luo, Si-Yuan Cao, Hong Gu, Huaqi Zhang, Hui-Liang Shen

We extract 2D feature map from images and transform the sparse depth map to point cloud to extract sparse 3D features.

Depth Completion

TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection

1 code implementation26 May 2023 Xue Zhang, Xiao-Han Zhang, Jiacheng Ying, Zehua Sheng, Heng Yu, Chunguang Li, Hui-Liang Shen

In this paper, we propose a novel target-aware fusion strategy for multispectral pedestrian detection, named TFDet.

Pedestrian Detection

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