Apache Beam provides an advanced unified programming model, allowing you to implement batch and streaming data processing jobs that can run on any execution engine. Apache Beam is:
· UNIFIED – Use a single programming model for both batch and streaming use cases.
· PORTABLE – Execute pipelines on multiple execution environments, including Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow.
· EXTENSIBLE – Write and share new SDKs, IO connectors, and transformation libraries. …
Google Brain Project
Google Brain is an unofficial name for a deep learning research project at Google. …
Supervised deep learning methods have shown promising results for the task of monocular depth estimation; but acquiring ground truth is costly, and prone to noise as well as inaccuracies. While synthetic datasets have been used to circumvent above problems, the resultant models do not generalize well to natural scenes due to the inherent domain shift. Recent adversarial approaches for domain adaption have performed well in mitigating the differences between the source and target domains. But these methods are mostly limited to a classification setup and do not scale well for fully-convolutional architectures. In this work, we propose AdaDepth – an unsupervised domain adaptation strategy for the pixel-wise regression task of monocular depth estimation. The proposed approach is devoid of above limitations through a) adversarial learning and b) explicit imposition of content consistency on the adapted target representation. Our unsupervised approach performs competitively with other established approaches on depth estimation tasks and achieves state-of-the-art results in a semi-supervised setting. …