Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
The HoloLens Navigation for Robots project is an open source repository to be included as a release in the Applied Robotics Research Library. It is a set of sample code to build software capable of…
The purpose of this project is to release a set of clinically relevant labels for an existing, publicly available dataset (https://fastmri.org). With permission from the fastMRI team at NYU, we have engaged third party labelers…
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark…
The Tip of the Tongue (ToT) dataset is from the paper Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification. It is comprised of 758 question/answer pairs scraped from the website iRememberThisMovie.com…
Microsoft sponsored and co-organized Indoor Location Competition 2.0 in 2021. 1446 contestants from more than 60 countries making up 1170 teams participated in this unique global event. In this competition, a first-of-its-kind large-scale indoor location…
An open source indexing subsystem that brings index-based query acceleration to Apache Spark™ and big data workloads.
This is a codebase for our recently released paper “Focal Self-attention for Local-Global Interactions in Vision Transformers”. It developed a new sparse self-attention mechanism called focal self-attention towards more effective and efficient vision transformers. The…
The subseasonal_data package provides an API for loading and manipulating the SubseasonalClimateUSA dataset developed for training and benchmarking subseasonal forecasting models. Here, subseasonal refers to climate and weather forecasts made 2-6 weeks in advance. See…
Data augmentation is proven to be effective in many NLU tasks, especially for those suffering from data scarcity. In this paper, we present a powerful and easy to deploy text augmentation framework, Data Boost, which…
