794 citations · 4.3k across the 55 of their papers we have counts for
8 papers · 1 filter
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…
LVreID: Person Re-Identification with Long Sequence Videos
Jianing Li, Shiliang Zhang, Jingdong Wang +2
This paper mainly establishes a large-scale Long sequence Video database for person re-IDentification (LVreID).
Human Pose Estimation using Global and Local Normalization
Ke Sun, Cuiling Lan, Junliang Xing +3
In this paper, we address the problem of estimating the positions of human joints, i.e., articulated pose estimation. Recent state-of-the-art solutions model two key issues, joint…
Rethink ReLU to Training Better CNNs
Gangming Zhao, Zhaoxiang Zhang, He Guan +2
Most of convolutional neural networks share the same characteristic: each convolutional layer is followed by a nonlinear activation layer where Rectified Linear Unit (ReLU) is the…
Deeply-Learned Part-Aligned Representations for Person Re-Identification
Liming Zhao, Xi Li, Jingdong Wang +1
In this paper, we address the problem of person re-identification, which refers to associating the persons captured from different cameras. We propose a simple yet effective human…
Orthogonal and Idempotent Transformations for Learning Deep Neural Networks
Jingdong Wang, Yajie Xing, Kexin Zhang +1
Identity transformations, used as skip-connections in residual networks, directly connect convolutional layers close to the input and those close to the output in deep neural netwo…
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…
Learning Correspondence Structures for Person Re-identification
Weiyao Lin, Yang Shen, Junchi Yan +4
This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification. We first introduce a boosting-ba…