One-Shot Object Detection

10 papers with code • 2 benchmarks • 2 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.

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.

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.

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 Everything with Few Examples

mlzxy/devit 22 Sep 2023

DE-ViT establishes new state-of-the-art results on all benchmarks.