SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

12 Nov 2019Yan WangWei-Lun ChaoKilian Q. WeinbergerLaurens van der Maaten

Few-shot learners aim to recognize new object classes based on a small number of labeled training examples. To prevent overfitting, state-of-the-art few-shot learners use meta-learning on convolutional-network features and perform classification using a nearest-neighbor classifier... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Few-Shot Image Classification Mini-Imagenet 5-way (1-shot) SimpleShot (CL2N-DenseNet) Accuracy 64.29 # 16
Few-Shot Image Classification Mini-Imagenet 5-way (5-shot) SimpleShot (CL2N-DenseNet) Accuracy 81.5 # 14

Methods used in the Paper


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