Water Tank Marine Debris - Matching Task

This is a sub-dataset containing data for the matching task. Two datasets are available at 96x96 pixel resolution:

• Same (S): The same objects are used to build the training, validation, and testing sets. All object classes are used. Training set contains 33096 images, validation set contains 7092 images, and test set also 7092 images.
• Different (D): Objects of class 0-5 (can, bottle, drink carton, chain, propeller, and tire) are used to build the training set, while a different set of objects is used to build the test set (classes 6-9, hook, valve, shampoo bottle, and standing bottle). This is a harder task and requires object-independent learning to match FLS image patches. Training set contains 39840 images, while the test set contains 7440 images.

The task is given a sample pair of images, decide if they match or not, meaning that they contain the same object under a different point of view. This is modeled as binary classification. Each sample has shape (2, 96, 96), where the first dimension selects the sample from a matching pair. Additional labels (match_type) are available for each sample to indicate how it was obtained from the main marine debris water tank dataset:

• ID 0: Object to object positive, same class in the match pair.
• ID 1: Object to object negative, different class in the match pair.
• ID 2: Object to background negative

This information can be used for fine-grained evaluation and to find biases in the learned matcher.