3 accepted papers
We focus on the problem of predicting future states of entities in complex, real-world driving scenarios. Previous research has approached this problem via low-level signals to predict short time horizons, and has not addressed how to leverage key assets relied upon heavily by industry self-driving…
Deep networks have recently enjoyed enormous success when applied to recognition and classification problems in computer vision [22, 32], but their use in graphics problems has been limited ([23, 7] are notable recent exceptions). In this work, we present a novel deep architecture that per- forms ne…
Despite significant recent advances in the field of face recognition [DeepFace, DeepId2], implementing face verification and recognition efficiently at scale presents serious challenges to current approaches. In this paper we present a system, called FaceNet, that directly learns a mapping from face…