Omkar2118/datasets huggingface dataset:
UofTPed50

**UofTPed50** is an object detection and tracking dataset which uses GPS to ground truth the position and velocity of a pedestrian.

It can be used for benchmarking the positional accuracy of 3D pedestrian detection. It contains accurate positioning information by attaching a GPS system to the pedestrian itself. This dataset consists of 50 sequences of varying distance, pedestrian trajectory, and ego-vehicle trajectory. Each sequence contains one pedestrian. The scenarios are broken into four groups.

Introducing paper: aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge
Human Optical Flow
Full name: Human Optical Flow dataset

A synthetic data of videos of human action sequences and the corresponding optical flow.

Introducing paper: Learning Human Optical Flow
Overruling

The **Overruling** dataset is a law dataset corresponding to the task of determining when a sentence is overruling a prior decision. This is a binary classification task, where positive examples are overruling sentences and negative examples are non-overruling sentences extracted from legal opinions. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent, by a constitutionally valid statute or a decision by the same or higher ranking court which establishes a different rule on the point of law involved. The Overruling dataset consists of 2,400 sentences.

To read more about the dataset, please see our [paper](https://arxiv.org/abs/2104.08671) or our [blogpost](https://reglab.stanford.edu/data/the-overruling-dataset-a-benchmark-for-detecting-legal-decisions-that-have-been-overruled/).

Introducing paper: When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset
Terms of Service

The **Terms of Service** dataset is a law dataset corresponding to the task of identifying whether contractual terms are potentially unfair. This is a binary classification task, where positive examples are potentially unfair contractual terms (clauses) from the terms of service in consumer contracts. Article 3 of the Directive 93/13 on Unfair Terms in Consumer Contracts defines an unfair contractual term as follows. A contractual term is unfair if: (1) it has not been individually negotiated; and (2) contrary to the requirement of good faith, it causes a significant imbalance in the parties rights and obligations, to the detriment of the consumer. The Terms of Service dataset consists of 9,414 examples.

Introducing paper: CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
NBA SportVU

The NBA SportVU dataset contains player and ball trajectories for 631 games from the 2015-2016 NBA season. The raw tracking data is in the JSON format, and each moment includes information about the identities of the players on the court, the identities of the teams, the period, the game clock, and the shot clock.