70 citations · 139 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…