11.7k citations · 12.3k across the 6 of their papers we have counts for
6 papers
FISHING Net: Future Inference of Semantic Heatmaps In Grids
Noureldin Hendy, Cooper Sloan, Feng Tian +5
For autonomous robots to navigate a complex environment, it is crucial to understand the surrounding scene both geometrically and semantically. Modern autonomous robots employ mult…
Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
Joey Hong, Benjamin Sapp, James Philbin
We focus on the problem of predicting future states of entities in complex, real-world driving scenarios. Previous research has used low-level signals to predict short time horizon…
PlaNet - Photo Geolocation with Convolutional Neural Networks
Tobias Weyand, Ilya Kostrikov, James Philbin
Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to co…
DeepStereo: Learning to Predict New Views from the World's Imagery
John Flynn, Ivan Neulander, James Philbin +1
Deep networks have recently enjoyed enormous success when applied to recognition and classification problems in computer vision, but their use in graphics problems has been limited…
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff, Dmitry Kalenichenko, James Philbin
Despite significant recent advances in the field of face recognition, implementing face verification and recognition efficiently at scale presents serious challenges to current app…
Learning Fine-grained Image Similarity with Deep Ranking
Jiang Wang, Yang song, Thomas Leung +5
Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences. This paper proposes a deep ranking model that em…