activity
20162019
most citedInterleaved Group Convolutions for Deep Neural Networks

80 citations · 81 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2019

Collaborative Quantization for Cross-Modal Similarity Search

Ting Zhang, Jingdong Wang

Cross-modal similarity search is a problem about designing a search system supporting querying across content modalities, e.g., using an image to search for texts or using a text t…

cs.CV20191 cited

Supervised Quantization for Similarity Search

Xiaojuan Wang, Ting Zhang, Guo-Jun Q +2

In this paper, we address the problem of searching for semantically similar images from a large database. We present a compact coding approach, supervised quantization. Our approac…

cs.CV2018

IGCV: Interleaved Structured Sparse Convolutional Neural Networks

Guotian Xie, Jingdong Wang, Ting Zhang +3

In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels. In add…

cs.CV2017

Composite Quantization

Jingdong Wang, Ting Zhang

This paper studies the compact coding approach to approximate nearest neighbor search. We introduce a composite quantization framework. It uses the composition of several () ele…

cs.CV201780 cited

Interleaved Group Convolutions for Deep Neural Networks

Ting Zhang, Guo-Jun Qi, Bin Xiao +1

In this paper, we present a simple and modularized neural network architecture, named interleaved group convolutional neural networks (IGCNets). The main point lies in a novel buil…

cs.CV2016

Deeply-Fused Nets

Jingdong Wang, Zhen Wei, Ting Zhang +1

In this paper, we present a novel deep learning approach, deeply-fused nets. The central idea of our approach is deep fusion, i.e., combine the intermediate representations of base…