Freesound Dataset 50k (or FSD50K for short) is an open dataset of human-labeled sound events containing 51,197 Freesound clips unequally distributed in 200 classes drawn from the AudioSet Ontology. FSD50K has been created at the Music Technology Group of Universitat Pompeu Fabra. It consists mainly of sound events produced by physical sound sources and production mechanisms, including human sounds, sounds of things, animals, natural sounds, musical instruments and more.
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GuitarSet is a dataset of high-quality guitar recordings and rich annotations. It contains 360 excerpts 30 seconds in length. The 360 excerpts are the result of the following combinations:
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The FIVR-200K dataset has been collected to simulate the problem of Fine-grained Incident Video Retrieval (FIVR). The dataset comprises 225,960 videos associated with 4,687 Wikipedia events and 100 selected video queries.
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Contains normal driving videos together with a set of anomalous actions in its training set. In the test set of the DAD dataset, there are unseen anomalous actions that still need to be winnowed out from normal driving.
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Millions of people around the world have low or no vision. Assistive software applications have been developed for a variety of day-to-day tasks, including currency recognition. To aid with this task, we present BankNote-Net, an open dataset for assistive currency recognition. The dataset consists of a total of 24,816 embeddings of banknote images captured in a variety of assistive scenarios, spanning 17 currencies and 112 denominations. These compliant embeddings were learned using supervised contrastive learning and a MobileNetV2 architecture, and they can be used to train and test specialized downstream models for any currency, including those not covered by our dataset or for which only a few real images per denomination are available (few-shot learning). We deploy a variation of this model for public use in the last version of the Seeing AI app developed by Microsoft, which has over a 100 thousand monthly active users.
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