Fast Single-shot Ship Instance Segmentation Based on Polar Template Mask in Remote Sensing Images
Object detection and instance segmentation in remote sensing images is a fundamental and challenging task, due to the complexity of scenes and targets. The latest methods tried to take into account both the efficiency and the accuracy of instance segmentation. In order to improve both of them, in this paper, we propose a single-shot convolutional neural network structure, which is conceptually simple and straightforward, and meanwhile makes up for the problem of low accuracy of single-shot networks. Our method, termed with SSS-Net, detects targets based on the location of the object's center and the distances between the center and the points on the silhouette sampling with non-uniform angle intervals, thereby achieving abalanced sampling of lines in mask generation. In addition, we propose a non-uniform polar template IoU based on the contour template in polar coordinates. Experiments on both the Airbus Ship Detection Challenge dataset and the ISAIDships dataset show that SSS-Net has strong competitiveness in precision and speed for ship instance segmentation.
Code (0)
등록된 구현이 없습니다.
Tasks
Instance Segmentationobject-detectionObject DetectionSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
DeeperLab: Single-Shot Image Parser
We present a single-shot, bottom-up approach for whole image parsing. Whole image parsing, also known as Panoptic Segmentation, generalizes the tasks of semantic segmentation for 'stuff' classes and instance segmentation…
GPUInstance SegmentationPanoptic SegmentationSegmentation+1CenterMask: single shot instance segmentation with point representation
In this paper, we propose a single-shot instance segmentation method, which is simple, fast and accurate. There are two main challenges for one-stage instance segmentation: object instances differentiation and pixel-wise…
Instance SegmentationObjectSegmentationSemantic SegmentationPolarMask: Single Shot Instance Segmentation with Polar Representation
In this paper, we introduce an anchor-box free and single shot instance segmentation method, which is conceptually simple, fully convolutional and can be used as a mask prediction module for instance segmentation, by eas…
Distance regressionInstance SegmentationObject Detectionregression+2Bounding Box Embedding for Single Shot Person Instance Segmentation
We present a bottom-up approach for the task of object instance segmentation using a single-shot model. The proposed model employs a fully convolutional network which is trained to predict class-wise segmentation masks a…
Instance SegmentationObjectSegmentationSemantic SegmentationMask Encoding for Single Shot Instance Segmentation
To date, instance segmentation is dominated by twostage methods, as pioneered by Mask R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP, mainly due to the difficulty of compactly repres…
Instance SegmentationSegmentationSemantic Segmentation