70 citations · 223 across the 19 of their papers we have counts for
19 papers
ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentation
Hanbo Bi, Yulong Xu, Ya Li +8
The Segment Anything Model (SAM), with its prompt-driven paradigm, exhibits strong generalization in generic segmentation tasks. However, applying SAM to remote sensing (RS) images…
RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretation
Hanbo Bi, Yingchao Feng, Boyuan Tong +11
The rapid advancement of foundation models has revolutionized visual representation learning in a self-supervised manner. However, their application in remote sensing (RS) remains…
AgMTR: Agent Mining Transformer for Few-shot Segmentation in Remote Sensing
Hanbo Bi, Yingchao Feng, Yongqiang Mao +4
Few-shot Segmentation (FSS) aims to segment the interested objects in the query image with just a handful of labeled samples (i.e., support images). Previous schemes would leverage…
Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation
Hanbo Bi, Yingchao Feng, Wenhui Diao +5
For more efficient generalization to unseen domains (classes), most Few-shot Segmentation (FSS) would directly exploit pre-trained encoders and only fine-tune the decoder, especial…
SCLNet: A Scale-Robust Complementary Learning Network for Object Detection in UAV Images
Xuexue Li
Most recent UAV (Unmanned Aerial Vehicle) detectors focus primarily on general challenge such as uneven distribution and occlusion. However, the neglect of scale challenges, which…
RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning
Wenhui Diao, Haichen Yu, Kaiyue Kang +8
Aerial Remote Sensing (ARS) vision tasks present significant challenges due to the unique viewing angle characteristics. Existing research has primarily focused on algorithms for s…
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,…
TAFormer: A Unified Target-Aware Transformer for Video and Motion Joint Prediction in Aerial Scenes
Liangyu Xu, Wanxuan Lu, Hongfeng Yu +5
As drone technology advances, using unmanned aerial vehicles for aerial surveys has become the dominant trend in modern low-altitude remote sensing. The surge in aerial video data…
Not Just Learning from Others but Relying on Yourself: A New Perspective on Few-Shot Segmentation in Remote Sensing
Hanbo Bi, Yingchao Feng, Zhiyuan Yan +4
Few-shot segmentation (FSS) is proposed to segment unknown class targets with just a few annotated samples. Most current FSS methods follow the paradigm of mining the semantics fro…
Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes
Jiang-Tian Zhai, Ze Feng, Jinhao Du +6
Modern autonomous driving systems are typically divided into three main tasks: perception, prediction, and planning. The planning task involves predicting the trajectory of the ego…
OGMN: Occlusion-guided Multi-task Network for Object Detection in UAV Images
Xuexue Li, Wenhui Diao, Yongqiang Mao +4
Occlusion between objects is one of the overlooked challenges for object detection in UAV images. Due to the variable altitude and angle of UAVs, occlusion in UAV images happens mo…
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,…
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…
Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection
Xiaonan Lu, Wenhui Diao, Yongqiang Mao +4
Few-shot object detection, expecting detectors to detect novel classes with a few instances, has made conspicuous progress. However, the prototypes extracted by existing meta-learn…
Learning to Evaluate Performance of Multi-modal Semantic Localization
Zhiqiang Yuan, Wenkai Zhang, Chongyang Li +6
Semantic localization (SeLo) refers to the task of obtaining the most relevant locations in large-scale remote sensing (RS) images using semantic information such as text. As an em…
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes
Yongqiang Mao, Zonghao Guo, Xiaonan Lu +2
Few-shot segmentation of point cloud remains a challenging task, as there is no effective way to convert local point cloud information to global representation, which hinders the g…
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,…