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Datasets

Greatest papers with code

One-Shot Instance Segmentation

28 Nov 2018bethgelab/siamese-mask-rcnn

We demonstrate empirical results on MS Coco highlighting challenges of the one-shot setting: while transferring knowledge about instance segmentation to novel object categories works very well, targeting the detection network towards the reference category appears to be more difficult.

FEW-SHOT OBJECT DETECTION ONE-SHOT INSTANCE SEGMENTATION ONE-SHOT LEARNING ONE-SHOT OBJECT DETECTION

Quasi-Dense Similarity Learning for Multiple Object Tracking

11 Jun 2020SysCV/qdtrack

In this paper, we present Quasi-Dense Similarity Learning, which densely samples hundreds of region proposals on a pair of images for contrastive learning.

METRIC LEARNING MULTI-OBJECT TRACKING MULTIPLE OBJECT TRACKING ONE-SHOT OBJECT DETECTION

OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features

ECCV 2020 aosokin/os2d

In this paper, we consider the task of one-shot object detection, which consists in detecting objects defined by a single demonstration.

ONE-SHOT OBJECT DETECTION

RepMet: Representative-based metric learning for classification and one-shot object detection

12 Jun 2018jshtok/RepMet

Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each category is represented by only a few examples.

CLASSIFICATION FEW-SHOT OBJECT DETECTION METRIC LEARNING OBJECT CLASSIFICATION ONE-SHOT OBJECT DETECTION

DroNet: Efficient convolutional neural network detector for real-time UAV applications

18 Jul 2018gplast/DroNet

Through the analysis we propose a CNN architecture that is capable of detecting vehicles from aerial UAV images and can operate between 5-18 frames-per-second for a variety of platforms with an overall accuracy of ~95%.

OBJECT DETECTION IN AERIAL IMAGES ONE-SHOT OBJECT DETECTION REAL-TIME OBJECT DETECTION

One-Shot Object Detection without Fine-Tuning

8 May 2020RyanXLi/OneshotDet

Deep learning has revolutionized object detection thanks to large-scale datasets, but their object categories are still arguably very limited.

METRIC LEARNING ONE-SHOT OBJECT DETECTION