1k citations · 7.4k across the 81 of their papers we have counts for
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Camera Style Adaptation for Person Re-identification
Zhun Zhong, Liang Zheng, Zhedong Zheng +2
Being a cross-camera retrieval task, person re-identification suffers from image style variations caused by different cameras. The art implicitly addresses this problem by learning…
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
Yifan Sun, Liang Zheng, Yi Yang +2
Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A…
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
Weijian Deng, Liang Zheng, Qixiang Ye +3
Person re-identification (re-ID) models trained on one domain often fail to generalize well to another. In our attempt, we present a "learning via translation" framework. In the ba…
Dual-Path Convolutional Image-Text Embeddings with Instance Loss
Zhedong Zheng, Liang Zheng, Michael Garrett +3
Matching images and sentences demands a fine understanding of both modalities. In this paper, we propose a new system to discriminatively embed the image and text to a shared visua…
Dynamic Label Graph Matching for Unsupervised Video Re-Identification
Mang Ye, Andy J Ma, Liang Zheng +2
Label estimation is an important component in an unsupervised person re-identification (re-ID) system. This paper focuses on cross-camera label estimation, which can be subsequentl…
Random Erasing Data Augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang +2
In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN). In training, Random Erasing randomly selects a recta…
PatchShuffle Regularization
Guoliang Kang, Xuanyi Dong, Liang Zheng +1
This paper focuses on regularizing the training of the convolutional neural network (CNN). We propose a new regularization approach named ``PatchShuffle`` that can be adopted in an…
Pedestrian Alignment Network for Large-scale Person Re-identification
Zhedong Zheng, Liang Zheng, Yi Yang
Person re-identification (person re-ID) is mostly viewed as an image retrieval problem. This task aims to search a query person in a large image pool. In practice, person re-ID usu…
Unsupervised Person Re-identification: Clustering and Fine-tuning
Hehe Fan, Liang Zheng, Yi Yang
The superiority of deeply learned pedestrian representations has been reported in very recent literature of person re-identification (re-ID). In this paper, we consider the more pr…
Few-Example Object Detection with Model Communication
Xuanyi Dong, Liang Zheng, Fan Ma +2
In this paper, we study object detection using a large pool of unlabeled images and only a few labeled images per category, named "few-example object detection". The key challenge…
Part-based Deep Hashing for Large-scale Person Re-identification
Fuqing Zhu, Xiangwei Kong, Liang Zheng +2
Large-scale is a trend in person re-identification (re-id). It is important that real-time search be performed in a large gallery. While previous methods mostly focus on discrimina…
Twitter100k: A Real-world Dataset for Weakly Supervised Cross-Media Retrieval
Yuting Hu, Liang Zheng, Yi Yang +1
This paper contributes a new large-scale dataset for weakly supervised cross-media retrieval, named Twitter100k. Current datasets, such as Wikipedia, NUS Wide and Flickr30k, have t…
A New Evaluation Protocol and Benchmarking Results for Extendable Cross-media Retrieval
Ruoyu Liu, Yao Zhao, Liang Zheng +2
This paper proposes a new evaluation protocol for cross-media retrieval which better fits the real-word applications. Both image-text and text-image retrieval modes are considered.…
Improving Person Re-identification by Attribute and Identity Learning
Yutian Lin, Liang Zheng, Zhedong Zheng +4
Person re-identification (re-ID) and attribute recognition share a common target at learning pedestrian descriptions. Their difference consists in the granularity. Most existing re…
SVDNet for Pedestrian Retrieval
Yifan Sun, Liang Zheng, Weijian Deng +1
This paper proposes the SVDNet for retrieval problems, with focus on the application of person re-identification (re-ID). We view each weight vector within a fully connected (FC) l…
Pose Invariant Embedding for Deep Person Re-identification
Liang Zheng, Yujia Huang, Huchuan Lu +1
Pedestrian misalignment, which mainly arises from detector errors and pose variations, is a critical problem for a robust person re-identification (re-ID) system. With bad alignmen…
Re-ranking Person Re-identification with k-reciprocal Encoding
Zhun Zhong, Liang Zheng, Donglin Cao +1
When considering person re-identification (re-ID) as a retrieval process, re-ranking is a critical step to improve its accuracy. Yet in the re-ID community, limited effort has been…
Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro
Zhedong Zheng, Liang Zheng, Yi Yang
The main contribution of this paper is a simple semi-supervised pipeline that only uses the original training set without collecting extra data. It is challenging in 1) how to obta…