1.4k citations · 2k across the 4 of their papers we have counts for
4 papers
Deep Cuboid Detection: Beyond 2D Bounding Boxes
Debidatta Dwibedi, Tomasz Malisiewicz, Vijay Badrinarayanan +1
We present a Deep Cuboid Detector which takes a consumer-quality RGB image of a cluttered scene and localizes all 3D cuboids (box-like objects). Contrary to classical approaches wh…
Training Deep Neural Networks on Noisy Labels with Bootstrapping
Scott Reed, Honglak Lee, Dragomir Anguelov +3
Current state-of-the-art deep learning systems for visual object recognition and detection use purely supervised training with regularization such as dropout to avoid overfitting.…
Self-informed neural network structure learning
David Warde-Farley, Andrew Rabinovich, Dragomir Anguelov
We study the problem of large scale, multi-label visual recognition with a large number of possible classes. We propose a method for augmenting a trained neural network classifier…
Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in th…