Object Localization
Found 6 free book(s)
Learning Deep Features for Discriminative Localization
cnnlocalization.csail.mit.eduWeakly-supervised object localization: There have been a number of recent works exploring weakly-supervised object localization using CNNs [1, 16, 2, 15]. Bergamoetal [1]propose atechniqueforself-taughtobject localization involving masking out image regions to iden-tify the regions causing the maximal activations in order to localize objects.
Learning Deep Features for Discriminative Localization
openaccess.thecvf.comWeakly-supervised object localization: There have been a number of recent works exploring weakly-supervised object localization using CNNs [1, 16, 2, 15]. Bergamoetal [1]propose atechniqueforself-taughtobject localization involving masking out image regions to iden-tify the regions causing the maximal activations in order to localize objects.
1 Object Detection in 20 Years: A Survey - arXiv
arxiv.orgobject detection include but not limited to the following aspects: object rotation and scale changes (e.g., small ob-jects), accurate object localization, dense and occluded object detection, speed up of detection, etc. In Sections 4 and 5, we will give a more detailed analysis of these topics. The rest of this paper is organized as follows. In ...
Generalized Intersection over Union: A Metric and A Loss ...
giou.stanford.edupopular object detection benchmarks such as PASCAL VOC and MS COCO. 1. Introduction Bounding box regression is one of the most fundamental components in many 2D/3D computer vision tasks. Tasks such as object localization, multiple object detection, ob-ject tracking and instance level segmentation rely on ac-curate bounding box regression.
Multi-Task Multi-Sensor Fusion for 3D Object Detection
openaccess.thecvf.com3D object detection focus on camera based solutions with monocular or stereo images [3, 2]. However, they suffer from the inherent difficulties of estimating depth from images and as a result perform poorly in 3D localization. More recent 3D object detectors rely on depth sensors such as LiDAR [34, 36]. However, although range sensors
Faster R-CNN: Towards Real-Time Object Detection with ...
arxiv.org1 Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun Abstract—State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, …