jsupancic/NestedParFor
A library for nested parallel-for-loops without over-subscription.
Implementation of the CVPR 2015 paper: Learning to propose objects
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A library for nested parallel-for-loops without over-subscription.
Python implementation of BING Objectness method from "BING: Binarized Normed Gradients for Objectness Estimation at 300fps".
Learning Rich Features from RGB-D Images for Object Detection and Segmentation
Caffe: a fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.