Figure A1: Comparative intrinsic dimensionality analysis of four different datasets

We then performed a PCA analysis on the embeddings from each dataset, looking at the variance explained as a function of the number of retained dimensions. We used the the objects being looked at by the child field to assemble a large collection of labeled frames for evaluation purposes. This field often includes multiple labels for each cell (a cell is the collection of frames between two consecutive time stamps). This reduced the final number of unique labels to 414. For evaluation purposes, we further modified this noisy labeled dataset as follows.