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Few-Shot Image Classification archive 2025-07-28

OMNIGLOT - 1-Shot, 20-way Benchmark (Few-Shot Image Classification)

20 rows 19 with code listed 1 metric

Few-Shot Image Classification is a computer vision task that involves training machine learning models to classify images into predefined categories using only a few labeled examples of each category (typically < 6 examples). The goal is to enable models to recognize and classify new images with minimal supervision and limited data, without having to train on large datasets. (typically < 6 examples)

The archive carries no text for this table; the description above is the archive's text for the task Few-Shot Image Classification. archive 2025-07-28

Over time archive 2025-07-28

The chart needs JavaScript; the table below carries every value.

Direction inferred from the metric name, not from the archive: Accuracy (higher is better). Points are placed at the row's paper date; 20 of 20 rows carry one.

Results archive 2025-07-28

Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.

Paper Code Ran Syntology Report
1 GCR 99.63 – Paper Code 2019 2 of 2 ran · 0 unverified report
2 DCN6-E 99.11 – Paper Code 2019 linked, not harvested report
3 DCN4 98.8% – Paper Code 2019 linked, not harvested report
4 TapNet 98.07% – Paper Code 2019 linked, not harvested report
5 MAML++ 97.7 – Paper Code 2022 linked, not harvested report
6 MAML++ 97.65 – Paper Code 2018 1 of 1 ran · 0 unverified report
7 Relation Net 97.6% – Paper Code 2017 1 of 2 ran · 1 unverified report
8 APL 97.2% – Paper Code 2019 linked, not harvested report
9 MT-net 96.2% – Paper Code 2018 linked, not harvested report
10 iMAML, Hessian-Free 96.18 – Paper Code 2019 27 of 36 ran · 9 unverified report
11 adaCNN (DF) 96.12% – Paper – 2017 no code linked report
12 Prototypical Networks 96% – Paper Code 2017 49 of 64 ran · 15 unverified report
13 Hyperbolic ProtoNet 95.9% – Paper Code 2019 4 of 6 ran · 2 unverified report
14 ConvNet with Memory Module 95% – Paper Code 2017 linked, not harvested report
15 Matching Nets 93.8% – Paper Code 2016 6 of 16 ran · 10 unverified report
16 Neural Statistician 93.2% – Paper Code 2016 2 of 14 ran · 12 unverified report
17 VAMPIRE 93.2 – Paper Code 2019 linked, not harvested report
18 Reptile + Transduction 89.43% – Paper Code 2018 24 of 42 ran · 18 unverified report
19 MC2+ 88% – Paper Code 2019 linked, not harvested report
20 MR-MAML 83.3 – Paper Code 2019 linked, not harvested report

All 20 rows shown. 20 link to a paper page on this site; 0 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28

Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 9 rows have a graph line, from 9 distinct papers; 9 rows (9 papers) have at least one sample that ran. Counting each paper once: Syntology ran 116 of 183 samples; 67 unverified. Separately, 51 of those 183 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-25. Per-sample status is on the paper page.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections