Object Detection via a Multi-Region and Semantic Segmentation-Aware CNN Model
We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting CNN-based representation aims at capturing a diverse set of discriminative appearance factors and exhibits localization sensitivity that is essential for accurate object localization. We exploit the above properties of our recognition module by integrating it on an iterative localization mechanism that alternates between scoring a box proposal and refining its location with a deep CNN regression model. Thanks to the efficient use of our modules, we detect objects with very high localization accuracy. On the detection challenges of PASCAL VOC2007 and PASCAL VOC2012 we achieve mAP of 78.2% and 73.9% correspondingly, surpassing any other published work by a significant margin.
Code (1)
Tasks
Objectobject-detectionObject DetectionObject LocalizationSemantic SegmentationSimilar Papers 제목 키워드 기반
Semantic Object Segmentation via Detection in Weakly Labeled Video
Semantic object segmentation in video is an important step for large-scale multimedia analysis. In many cases, however, semantic objects are only tagged at video-level, making them difficult to be located and segmented. …
Objectobject-detectionObject DetectionSegmentation+1Object detection via a multi-region & semantic segmentation-aware CNN model
We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting CNN-based representation aims at capturing…
Objectobject-detectionObject DetectionObject Localization+2MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
In this work, we tackle the problem of instance segmentation, the task of simultaneously solving object detection and semantic segmentation. Towards this goal, we present a model, called MaskLab, which produces three out…
Instance SegmentationObjectobject-detectionObject Detection+3Fused Text Segmentation Networks for Multi-oriented Scene Text Detection
In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instance-aware semantic segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-lev…
Multi-Oriented Scene Text Detectionobject-detectionObject DetectionRegion Proposal+5Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks
We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs). COB is computational…
Boundary DetectionContour Detectionimage-classificationImage Classification+6