Search Results for author: Hanbo Bi

Found 4 papers, 1 papers with code

Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes

no code implementations30 May 2024 Yong-Qiang Mao, Hanbo Bi, Xuexue Li, Kaiqiang Chen, Zhirui Wang, Xian Sun, Kun fu

Thanks to the application of deep learning technology in point cloud processing of the remote sensing field, point cloud segmentation has become a research hotspot in recent years, which can be applied to real-world 3D, smart cities, and other fields.

Point Cloud Segmentation Segmentation +1

SDL-MVS: View Space and Depth Deformable Learning Paradigm for Multi-View Stereo Reconstruction in Remote Sensing

no code implementations27 May 2024 Yong-Qiang Mao, Hanbo Bi, Liangyu Xu, Kaiqiang Chen, Zhirui Wang, Xian Sun, Kun fu

To solve the above problem, we re-examine the deformable learning method in the Multi-View Stereo task and propose a novel paradigm based on view Space and Depth deformable Learning (SDL-MVS), aiming to learn deformable interactions of features in different view spaces and deformably model the depth ranges and intervals to enable high accurate depth estimation.

3D Reconstruction Depth Estimation

TAFormer: A Unified Target-Aware Transformer for Video and Motion Joint Prediction in Aerial Scenes

no code implementations27 Mar 2024 Liangyu Xu, Wanxuan Lu, Hongfeng Yu, Yongqiang Mao, Hanbo Bi, Chenglong Liu, Xian Sun, Kun fu

To address this issue, we introduce a novel task called Target-Aware Aerial Video Prediction, aiming to simultaneously predict future scenes and motion states of the target.

Disaster Response Object Tracking +1

Not Just Learning from Others but Relying on Yourself: A New Perspective on Few-Shot Segmentation in Remote Sensing

1 code implementation19 Oct 2023 Hanbo Bi, Yingchao Feng, Zhiyuan Yan, Yongqiang Mao, Wenhui Diao, Hongqi Wang, Xian Sun

In addition, to prevent the co-existence of multiple classes in remote sensing scenes from exacerbating the collapse of FSS generalization, we also propose a new Known-class Meta Suppressor (KMS) module to suppress the activation of known-class objects in the sample.

Image Segmentation Semantic Segmentation

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