Resources

Datasets

Large-scale datasets and benchmarks for training, evaluating, and testing models to measure and advance AI progress.

Featured Dataset

FACET Dataset

FACET is a comprehensive benchmark dataset designed for measuring or evaluating the robustness and algorithmic fairness of AI and machine-learning vision models for protected groups.

Overview

Datasets

EgoTV Dataset

A benchmark and dataset for systematic investigation of vision-language models on compositional, causal (e.g., effect of actions), and temporal (e.g., action ordering) reasoning in egocentric settings.

MMCSG Dataset

The MMCSG (Multi-Modal Conversations in Smart Glasses) dataset comprises two-sided conversations recorded using Aria glasses, featuring multi-modal data such as multi-channel audio, video, accelerometer, and gyroscope measurements.

Speech Fairness Dataset

Designed for training general-purpose object segmentation models from open world images.

Casual Conversations V2

For evaluating computer vision, audio and speech models for accuracy across a diverse set of ages, genders, language/dialects, geographies, disabilities, and more.

Casual Conversations

For evaluating computer vision and audio models for accuracy across a diverse set of age, genders, apparent skin tones and ambient lighting conditions.

Common Objects in 3D (CO3D)

For learning category-specific 3D reconstruction and new-view synthesis using multi-view images of common object categories.

Segment Anything

Designed for training general-purpose object segmentation models from open world images.

DISC21 Dataset

Helps researchers evaluate their image copy detection models for accuracy.

EgoObjects Dataset

A project that seeks to advance the fundamental AI research needed for multi-modal machine perception for first-person video understanding.

FLoRes Benchmarking Dataset

Used for machine translation between English and low-resource languages.

Ego4d

Ego4D is a collaborative project, seeking to advance the fundamental AI research needed for multimodal machine perception for first-person video understanding.

Frameworks and tools

Sharing our ML frameworks and tools with the community to collaborate and accelerate AI advancement

Models and Libraries

Our open-sourced libraries and models for those taking our AI learnings further through software and app development

Demos

Our demos for anyone wanting to experience our latest research breakthroughs first hand

System cards

Multiple machine learning (ML) models that help people understand the intention, impact and limitations of our AI systems

Publications

Our library of published papers to learn about our latest AI breakthroughs and innovations