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Found 7 papers, 5 papers with code
FISHING Net: Future Inference of Semantic Heatmaps In Grids
Managing the different reference frames and characteristics of the sensors, and merging their observations into a single representation complicates perception.
Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
We focus on the problem of predicting future states of entities in complex, real-world driving scenarios.
PlaNet - Photo Geolocation with Convolutional Neural Networks
Is it possible to build a system to determine the location where a photo was taken using just its pixels?
Ranked #1 on
Photo geolocation estimation
on Im2GPS
(Reference images metric)
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
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.
Ranked #5 on
Fine-Grained Image Classification
on CUB-200-2011
(using extra training data)
DeepStereo: Learning to Predict New Views from the World's Imagery
To our knowledge, our work is the first to apply deep learning to the problem of new view synthesis from sets of real-world, natural imagery.
FaceNet: A Unified Embedding for Face Recognition and Clustering
On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99. 63%.
Ranked #1 on
Disguised Face Verification
on MegaFace
Learning Fine-grained Image Similarity with Deep Ranking
This paper proposes a deep ranking model that employs deep learning techniques to learn similarity metric directly from images. It has higher learning capability than models based on hand-crafted features.
