데이터셋 탐색

The Sprites dataset contains 60 pixel color images of animated characters (sprites). There are 672 sprites, 500 for training, 100 for testing and 72 for validation. Each sprite has 20 animations and 178 images, so the full dataset has 120K images in total. There are many changes in the appearance of the sprites, they differ in their body shape, gender, hair, armor, arm type, greaves, and weapon. Source: Challenges in Disentangling Independent Factors of Variation

dSprites is a dataset of 2D shapes procedurally generated from 6 ground truth independent latent factors. These factors are color, shape, scale, rotation, x and y positions of a sprite. All possible combinations of these latents are present exactly once, generating N = 737280 total images. Source: dSprites

This csv consists of (x-position, y-position, area) tuples of three views (left, middle, right) of downscaled binary masks with aspect ratio kept (64 x 128) from the 2019 YouTube-VIS challenge, which can be found at https://competitions.codalab.org/competitions/20127#participate-get-data. Extracting pairs from this csv results in 234,652 transitions in the given statistics. These statistics can be used to augment ground truth factor distributions with natural transitions, which we demonstrate with spriteworld. For details, we refer to our paper, which can be found at https://openreview.net/forum?id=EbIDjBynYJ8.

Easily generate simple continual learning benchmarks. Inspired by dSprites. > It allows for procedurally generating a virtually infinite progression of random two-dimensional shapes. [...] we generate each unique shape in every combination of orientation, scale, and position. Most importantly, by providing the ground truth values of individual factors of variation (FoVs)