1k citations · 1.4k across the 12 of their papers we have counts for
4 papers · 2 filters
Compressing Deep Convolutional Networks using Vector Quantization
Yunchao Gong, Liu Liu, Ming Yang +1
Deep convolutional neural networks (CNN) has become the most promising method for object recognition, repeatedly demonstrating record breaking results for image classification and…
Learning Spatiotemporal Features with 3D Convolutional Networks
Du Tran, Lubomir Bourdev, Rob Fergus +2
We propose a simple, yet effective approach for spatiotemporal feature learning using deep 3-dimensional convolutional networks (3D ConvNets) trained on a large scale supervised vi…
Deep Poselets for Human Detection
Lubomir Bourdev, Fei Yang, Rob Fergus
We address the problem of detecting people in natural scenes using a part approach based on poselets. We propose a bootstrapping method that allows us to collect millions of weakly…
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie +7
We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question…