Instance segmentation of buildings using keypoints
Building segmentation is of great importance in the task of remote sensing imagery interpretation. However, the existing semantic segmentation and instance segmentation methods often lead to segmentation masks with blurred boundaries. In this paper, we propose a novel instance segmentation network for building segmentation in high-resolution remote sensing images. More specifically, we consider segmenting an individual building as detecting several keypoints. The detected keypoints are subsequently reformulated as a closed polygon, which is the semantic boundary of the building. By doing so, the sharp boundary of the building could be preserved. Experiments are conducted on selected Aerial Imagery for Roof Segmentation (AIRS) dataset, and our method achieves better performance in both quantitative and qualitative results with comparison to the state-of-the-art methods. Our network is a bottom-up instance segmentation method that could well preserve geometric details.
Code (0)
등록된 구현이 없습니다.
Tasks
Instance SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
Pose2Instance: Harnessing Keypoints for Person Instance Segmentation
Human keypoints are a well-studied representation of people.We explore how to use keypoint models to improve instance-level person segmentation. The main idea is to harness the notion of a distance transform of oracle pr…
Instance SegmentationSegmentationSemantic Segmentation3D Instance Segmentation of MVS Buildings
We present a novel 3D instance segmentation framework for Multi-View Stereo (MVS) buildings in urban scenes. Unlike existing works focusing on semantic segmentation of urban scenes, the emphasis of this work lies in dete…
3D Instance SegmentationInstance SegmentationSegmentationSemantic SegmentationA Histogram Thresholding Improvement to Mask R-CNN for Scalable Segmentation of New and Old Rural Buildings
Mapping new and old buildings are of great significance for understanding socio-economic development in rural areas. In recent years, deep neural networks have achieved remarkable building segmentation results in high-re…
Instance SegmentationSegmentationSemantic SegmentationKeypoints as Dynamic Centroids for Unified Human Pose and Segmentation
The dynamic movement of the human body presents a fundamental challenge for human pose estimation and body segmentation. State-of-the-art approaches primarily rely on combining keypoint heatmaps with segmentation masks b…
Keypoint DetectionPose EstimationSegmentationDeep Affinity Net: Instance Segmentation via Affinity
Most of the modern instance segmentation approaches fall into two categories: region-based approaches in which object bounding boxes are detected first and later used in cropping and segmenting instances; and keypoint-ba…
Clusteringgraph partitioningInstance SegmentationSemantic Segmentation