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Few-Shot Object Detection

8 papers with code · Computer Vision
Subtask of Object Detection

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Frustratingly Simple Few-Shot Object Detection

16 Mar 2020ucbdrive/few-shot-object-detection

Such a simple approach outperforms the meta-learning methods by roughly 2~20 points on current benchmarks and sometimes even doubles the accuracy of the prior methods.

FEW-SHOT OBJECT DETECTION META-LEARNING

Few-shot Object Detection via Feature Reweighting

ICCV 2019 bingykang/Fewshot_Detection

The feature learner extracts meta features that are generalizable to detect novel object classes, using training data from base classes with sufficient samples.

FEW-SHOT LEARNING FEW-SHOT OBJECT DETECTION IMAGE CLASSIFICATION

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

CVPR 2020 fanq15/Few-Shot-Object-Detection-Dataset

To train our network, we contribute a new dataset that contains 1000 categories of various objects with high-quality annotations.

FEW-SHOT OBJECT DETECTION

Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning

ICCV 2019 yanxp/MetaR-CNN

Resembling the rapid learning capability of human, low-shot learning empowers vision systems to understand new concepts by training with few samples.

FEW-SHOT OBJECT DETECTION META-LEARNING SEMANTIC SEGMENTATION

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.

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

Meta-learning algorithms for Few-Shot Computer Vision

30 Sep 2019ebennequin/FewShotVision

Few-Shot Learning is the challenge of training a model with only a small amount of data.

FEW-SHOT IMAGE CLASSIFICATION FEW-SHOT OBJECT DETECTION

Context-Transformer: Tackling Object Confusion for Few-Shot Detection

16 Mar 2020Ze-Yang/Context-Transformer

Few-shot object detection is a challenging but realistic scenario, where only a few annotated training images are available for training detectors.

FEW-SHOT LEARNING FEW-SHOT OBJECT DETECTION TRANSFER LEARNING