Datasets › SHAPES
SHAPES (Swarm Heuristics based Adaptive and Penalized Estimation of Splines)
SHAPES is a dataset of synthetic images designed to benchmark systems for understanding of spatial and logical relations among multiple objects. The dataset consists of complex questions about arrangements of colored shapes. The questions are built around compositions of concepts and relations, e.g. Is there a red shape above a circle? or Is a red shape blue?. Questions contain between two and four attributes, object types, or relationships. There are 244 questions and 15,616 images in total, with all questions having a yes and no answer (and corresponding supporting image). This eliminates the risk of learning biases.
Each image is a 30×30 RGB image depicting a 3×3 grid of objects. Each object is characterized by shape (circle, square, triangle), colour (red, green, blue) and size (small, big).
Source: Visual Question Answering: A Survey of Methods and Datasets Image Source: https://github.com/ronghanghu/n2nmn#train-and-evaluate-on-the-shapes-dataset
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Time Series Classification | SHAPES | GP-Sig Accuracy 1.000 | Bayesian Learning from Sequential Data using Gaussian... | tgcsaba/GPSig | 9 | Compare |
Papers archive 2025-07-28
3 shown of 3 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 120. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections | 1 | 2 | 12 Jun 2020 | not harvested |
| Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | 1 | 6 | 19 Jun 2019 | ran 0 of 6 samples (6 unverified) |
| Multivariate LSTM-FCNs for Time Series Classification | 7 | 1 | 14 Jan 2018 | ran 2 of 2 samples (0 unverified; 2 pointer-only for licence) |
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- SHAPES
1 variant name, as the archive lists them.
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