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What Do Deep CNNs Learn About Objects?
Deep convolutional neural networks learn extremely powerful image representations, yet most of that power is hidden in the millions of deep-layer parameters.
Learning Deep Object Detectors from 3D Models
Crowdsourced 3D CAD models are becoming easily accessible online, and can potentially generate an infinite number of training images for almost any object category. We show that augmenting the training data of contemporary Deep Convolutional Neural Net (DCNN) models with such synthetic data can be effective, especially when real training data is limited or not well matched to the target domain.
Confidence-Rated Multiple Instance Boosting for Object Detection
In this paper, we propose a new MIL method for object detection that is capable of handling the noisier automatically obtained annotations.
