Omkar2118/datasets huggingface dataset:
RVSD
Full name: Realistic Video DeSnowing Dataset

Realistic Video DeSnowing Dataset (RVSD) contains a total of 110 pairs of videos. Each pair contains snowy and hazy videos and corresponding snow-free and haze-free ground truth videos. We use a rendering engine (Unreal Engine 5) and various augmentation techniques to generate snow and haze with diverse and realistic physical properties. This results in more realistic and varied synthesized videos, which improve the model’s performance on real-world data.

Introducing paper: Snow Removal in Video: A New Dataset and A Novel Method
address_parser_data

This is a set of datasets containing three versions of data:

- V0: the original sampled addresses with no augmentation.
- V1: Given V0, we apply basic cleaning and address structure masking technique (rearrangement or removal, but no addition of augmented address parts).
- V2: Given V0, we apply more advanced augmentation techniques (see paper for more info)

For each version we have three types of dataset:

- Train: around 3M datapoints used for training
- Test: around 100k datapoints used for testing
- Zero-shot: around 300k datapoints used for validation, extracting from addresses in countries not seen in train and test

Introducing paper: Fighting crime with Transformers: Empirical analysis of address parsing methods in payment data