637 citations · 779 across the 9 of their papers we have counts for
9 papers
Physics Inspired Hybrid Attention for SAR Target Recognition
Zhongling Huang, Chong Wu, Xiwen Yao +3
There has been a recent emphasis on integrating physical models and deep neural networks (DNNs) for SAR target recognition, to improve performance and achieve a higher level of phy…
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
Nian Liu, Kepan Nan, Wangbo Zhao +7
Few-Shot Video Object Segmentation (FSVOS) aims to segment objects in a query video with the same category defined by a few annotated support images. However, this task was seldom…
Progressively Dual Prior Guided Few-shot Semantic Segmentation
Qinglong Cao, Yuntian Chen, Xiwen Yao +1
Few-shot semantic segmentation task aims at performing segmentation in query images with a few annotated support samples. Currently, few-shot segmentation methods mainly focus on l…
Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation
Yuanwei Liu, Nian Liu, Xiwen Yao +1
Few-shot semantic segmentation aims to segment the target objects in query under the condition of a few annotated support images. Most previous works strive to mine more effective…
Towards Large-Scale Small Object Detection: Survey and Benchmarks
Gong Cheng, Xiang Yuan, Xiwen Yao +4
With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactor…
Learning Non-target Knowledge for Few-shot Semantic Segmentation
Yuanwei Liu, Nian Liu, Qinglong Cao +3
Existing studies in few-shot semantic segmentation only focus on mining the target object information, however, often are hard to tell ambiguous regions, especially in non-target r…
Physically Explainable CNN for SAR Image Classification
Zhongling Huang, Xiwen Yao, Ying Liu +3
Integrating the special electromagnetic characteristics of Synthetic Aperture Radar (SAR) in deep neural networks is essential in order to enhance the explainability and physics aw…
Oriented R-CNN for Object Detection
Xingxing Xie, Gong Cheng, Jiabao Wang +2
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bo…
Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning
Jinglin Xu, Wenbin Li, Jiantao Shen +5
As a concrete application of multi-view learning, multi-view classification improves the traditional classification methods significantly by integrating various views optimally. Al…