1k citations · 1.4k across the 5 of their papers we have counts for
6 papers
On Binary Embedding using Circulant Matrices
Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar +2
Binary embeddings provide efficient and powerful ways to perform operations on large scale data. However binary embedding typically requires long codes in order to preserve the dis…
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…
Circulant Binary Embedding
Felix X. Yu, Sanjiv Kumar, Yunchao Gong +1
Binary embedding of high-dimensional data requires long codes to preserve the discriminative power of the input space. Traditional binary coding methods often suffer from very high…
Multi-scale Orderless Pooling of Deep Convolutional Activation Features
Yunchao Gong, Liwei Wang, Ruiqi Guo +1
Deep convolutional neural networks (CNN) have shown their promise as a universal representation for recognition. However, global CNN activations lack geometric invariance, which li…
Deep Convolutional Ranking for Multilabel Image Annotation
Yunchao Gong, Yangqing Jia, Thomas Leung +2
Multilabel image annotation is one of the most important challenges in computer vision with many real-world applications. While existing work usually use conventional visual featur…
A Multi-View Embedding Space for Modeling Internet Images, Tags, and their Semantics
Yunchao Gong, Qifa Ke, Michael Isard +1
This paper investigates the problem of modeling Internet images and associated text or tags for tasks such as image-to-image search, tag-to-image search, and image-to-tag search (i…