67 citations · 115 across the 10 of their papers we have counts for
11 papers
SA-Occ: Satellite-Assisted 3D Occupancy Prediction in Real World
Chen Chen, Zhirui Wang, Taowei Sheng +8
Existing vision-based 3D occupancy prediction methods are inherently limited in accuracy due to their exclusive reliance on street-view imagery, neglecting the potential benefits o…
SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing
Chen Chen, Liangjin Zhao, Yuanchun He +5
Semantic segmentation and 3D reconstruction are two fundamental tasks in remote sensing, typically treated as separate or loosely coupled tasks. Despite attempts to integrate them…
SDL-MVS: View Space and Depth Deformable Learning Paradigm for Multi-View Stereo Reconstruction in Remote Sensing
Yong-Qiang Mao, Hanbo Bi, Liangyu Xu +4
Research on multi-view stereo based on remote sensing images has promoted the development of large-scale urban 3D reconstruction. However, remote sensing multi-view image data suff…
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes
Yong-Qiang Mao, Hanbo Bi, Xuexue Li +4
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,…
RingMo-lite: A Remote Sensing Multi-task Lightweight Network with CNN-Transformer Hybrid Framework
Yuelei Wang, Ting Zhang, Liangjin Zhao +9
In recent years, remote sensing (RS) vision foundation models such as RingMo have emerged and achieved excellent performance in various downstream tasks. However, the high demand f…
DCP-Net: A Distributed Collaborative Perception Network for Remote Sensing Semantic Segmentation
Zhechao Wang, Peirui Cheng, Shujing Duan +4
Onboard intelligent processing is widely applied in emergency tasks in the field of remote sensing. However, it is predominantly confined to an individual platform with a limited o…
LIGHT: Joint Individual Building Extraction and Height Estimation from Satellite Images through a Unified Multitask Learning Network
Yongqiang Mao, Xian Sun, Xingliang Huang +1
Building extraction and height estimation are two important basic tasks in remote sensing image interpretation, which are widely used in urban planning, real-world 3D construction,…
SiamTHN: Siamese Target Highlight Network for Visual Tracking
Jiahao Bao, Kaiqiang Chen, Xian Sun +3
Siamese network based trackers develop rapidly in the field of visual object tracking in recent years. The majority of siamese network based trackers now in use treat each channel…
Elevation Estimation-Driven Building 3D Reconstruction from Single-View Remote Sensing Imagery
Yongqiang Mao, Kaiqiang Chen, Liangjin Zhao +7
Building 3D reconstruction from remote sensing images has a wide range of applications in smart cities, photogrammetry and other fields. Methods for automatic 3D urban building mod…
Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification
Yongqiang Mao, Kaiqiang Chen, Wenhui Diao +4
The classification of airborne laser scanning (ALS) point clouds is a critical task of remote sensing and photogrammetry fields. Although recent deep learning-based methods have ac…
Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoders
Yongqiang Mao, Xian Sun, Kaiqiang Chen +4
Semantic segmentation of point clouds generates comprehensive understanding of scenes through densely predicting the category for each point. Due to the unicity of receptive field,…