We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with...
We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with...
Presto is an open-source distributed SQL query engine that supports analytics workloads involving multiple exabyte-scale data sources. Presto is used for low-latency interactive...
In this paper, we present AGRoL, a novel conditional diffusion model specially purposed to track full bodies given sparse upper-body tracking signals. Our model uses a simple...
To address these issues, we propose a novel framework Feature Representation Learning with adaptive Displacement Generation and Transformer fusion (FRL-DGT), in which a...
In this work, we propose LA-VocE, a new two-stage approach that predicts mel-spectrograms from noisy audiovisual speech via a transformer-based architecture, and then converts...
To combat this issue, we propose a proactive scheme for manipulation localization, termed MaLP. We encrypt the real images by adding a learned template. If the image is...
We propose a learning objective that formalizes differences in perceptual quality, by using domain knowledge of acoustic-phonetics.
In this paper we highlight open research problems and challenges from an industrial perspective. This perspective draws on our experience at Meta Platforms, which has been...
This is the first work to report on inferential testing at scale in industry. Specifically, it reports the experience of automated testing of integrity systems at Meta. We built...
We present RecD (Recommendation Deduplication), a suite of end-to-end infrastructure optimizations across the Deep Learning Recommendation Model (DLRM) training pipeline.