A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification
This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation-based semantic features (SSFs). These features represent, per segmentation-category, the pixel count, as well as the 2D average position and respective standard deviation values. Moreover, a two-branch network, GS2F2App, that exploits CNN-based global features extracted from RGB images and the segmentation-based features extracted from the proposed SSFs, is also proposed. GS2F2App was evaluated in two indoor scene benchmark datasets: the SUN RGB-D and the NYU Depth V2, achieving state-of-the-art results on both datasets.
Code (0)
등록된 구현이 없습니다.
Tasks
PositionScene ClassificationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
JSMNet Improving Indoor Point Cloud Semantic and Instance Segmentation through Self-Attention and Multiscale
The semantic understanding of indoor 3D point cloud data is crucial for a range of subsequent applications, including indoor service robots, navigation systems, and digital twin engineering. Global features are crucial f…
Instance SegmentationSegmentationSemantic SegmentationGlobal-Local Propagation Network for RGB-D Semantic Segmentation
Depth information matters in RGB-D semantic segmentation task for providing additional geometric information to color images. Most existing methods exploit a multi-stage fusion strategy to propagate depth feature to the …
DecoderScene SegmentationSegmentationSemantic SegmentationRDFNet: RGB-D Multi-Level Residual Feature Fusion for Indoor Semantic Segmentation
In multi-class indoor semantic segmentation using RGB-D data, it has been shown that incorporating depth feature into RGB feature is helpful to improve segmentation accuracy. However, previous studies have not fully expl…
SegmentationSemantic SegmentationGeometry-Aware Distillation for Indoor Semantic Segmentation
It has been shown that jointly reasoning the 2D appearance and 3D information from RGB-D domains is beneficial to indoor scene semantic segmentation. However, most existing approaches require accurate depth map as input …
SegmentationSemantic SegmentationExploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification
Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Despite the significant performance boost in…
object-detectionObject DetectionScene ClassificationSegmentation+1