James Philbin
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View article: FISHING Net: Future Inference of Semantic Heatmaps In Grids
FISHING Net: Future Inference of Semantic Heatmaps In Grids Open
For autonomous robots to navigate a complex environment, it is crucial to understand the surrounding scene both geometrically and semantically. Modern autonomous robots employ multiple sets of sensors, including lidars, radars, and cameras…
View article: Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions Open
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 horizons, and has not addressed how to leverage key assets relied …
View article: The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition Open
Current approaches for fine-grained recognition do the following: First, recruit experts to annotate a dataset of images, optionally also collecting more structured data in the form of part annotations and bounding boxes. Second, train a m…
View article: Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format
Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format Open
The digital imaging and communications in medicine (DICOM) information model combines pixel data and its metadata in a single object. There are user scenarios that only need metadata manipulation, such as deidentification and study migrati…
View article: DeepStereo: Learning to Predict New Views from the World's Imagery
DeepStereo: Learning to Predict New Views from the World's Imagery Open
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. In this work, we present a novel deep architecture that p…