One-Shot Object Detection

10 papers with code • 2 benchmarks • 3 datasets

( Image credit: Siamese Mask R-CNN )

Most implemented papers

One-Shot Instance Segmentation

bethgelab/siamese-mask-rcnn 28 Nov 2018

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.

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

gplast/DroNet 18 Jul 2018

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%.

One-Shot Object Detection with Co-Attention and Co-Excitation

timy90022/One-Shot-Object-Detection NeurIPS 2019

This paper aims to tackle the challenging problem of one-shot object detection.

Quasi-Dense Similarity Learning for Multiple Object Tracking

SysCV/qdtrack CVPR 2021

Compared to methods with similar detectors, it boosts almost 10 points of MOTA and significantly decreases the number of ID switches on BDD100K and Waymo datasets.

Simple Open-Vocabulary Object Detection with Vision Transformers

google-research/scenic 12 May 2022

Combining simple architectures with large-scale pre-training has led to massive improvements in image classification.

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

jshtok/RepMet 12 Jun 2018

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.

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

aosokin/os2d ECCV 2020

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 without Fine-Tuning

RyanXLi/OneshotDet 8 May 2020

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

Balanced and Hierarchical Relation Learning for One-Shot Object Detection

hero-y/bhrl CVPR 2022

In this paper, we introduce the balanced and hierarchical learning for our detector.

Detect Every Thing with Few Examples

mlzxy/devit 22 Sep 2023

For COCO, DE-ViT outperforms the open-vocabulary SoTA by 6. 9 AP50 and achieves 50 AP50 in novel classes.