Featured Dataset
SA-V Dataset
SA-V is a dataset designed for training general-purpose object segmentation models from open world videos. The dataset was introduced in our paper “Segment Anything 2”.
Datasets
Reality Labs Research Conversations for Hearing Augmentation Technology (RL-R CHAT)
The RL-R Conversations for Hearing Augmentation Technology (RL-R CHAT) dataset is an egocentric, multi-modal dataset created for tasks related to improved hearing, such as estimating listening effort, identifying sound sources of interest, and speech enhancement. Using the Project Aria platform, a large dataset was created of group conversations in quiet and noisy backgrounds involving familiar participants with and without hearing loss.
Multi-room Apartments Simulation (MRAS) Dataset
The Multi-Room Apartments Simulation (MRAS) dataset is a multi-modal dataset created for the task of estimating spatially-distributed acoustic parameters in complex scenes. It includes a large collection of scene geometries and Room-impulse Responses (RIRs), simulated from dozens of unique source positions and a dense grid of receivers.
Meta Synthetic Environments Lidar Dataset
The Meta Synthetic Environments (MSE) Lidar Dataset is the first-of-its-kind large-scale single-photon lidar dataset, built on top of Aria Synthetic Environments (ASE) and intended to unlock new machine learning capabilities for single-photon lidars.
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.
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
By releasing this dataset, we hope to further motivate the AI community to make strides toward improving the fairness of speech recognition models, which will help all users have a better experience using applications with ASR.
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.
Ego4d
Ego4D is a collaborative project, seeking to advance the fundamental AI research needed for multimodal machine perception for first-person video understanding.
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