1k citations · 7k across the 61 of their papers we have counts for
8 papers · 2 filters
Similarity-preserving Image-image Domain Adaptation for Person Re-identification
Weijian Deng, Liang Zheng, Qixiang Ye +2
This article studies the domain adaptation problem in person re-identification (re-ID) under a "learning via translation" framework, consisting of two components, 1) translating th…
SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation
Xiaolin Zhang, Yunchao Wei, Yi Yang +1
One-shot image semantic segmentation poses a challenging task of recognizing the object regions from unseen categories with only one annotated example as supervision. In this paper…
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation
Yawei Luo, Liang Zheng, Tao Guan +2
We consider the problem of unsupervised domain adaptation in semantic segmentation. The key in this campaign consists in reducing the domain shift, i.e., enforcing the data distrib…
Query Attack via Opposite-Direction Feature:Towards Robust Image Retrieval
Zhedong Zheng, Liang Zheng, Yi Yang +1
Most existing works of adversarial samples focus on attacking image recognition models, while little attention is paid to the image retrieval task. In this paper, we identify two i…
Self-produced Guidance for Weakly-supervised Object Localization
Xiaolin Zhang, Yunchao Wei, Guoliang Kang +2
Weakly supervised methods usually generate localization results based on attention maps produced by classification networks. However, the attention maps exhibit the most discrimina…
Macro-Micro Adversarial Network for Human Parsing
Yawei Luo, Zhedong Zheng, Liang Zheng +3
In human parsing, the pixel-wise classification loss has drawbacks in its low-level local inconsistency and high-level semantic inconsistency. The introduction of the adversarial n…
Adversarial Complementary Learning for Weakly Supervised Object Localization
Xiaolin Zhang, Yunchao Wei, Jiashi Feng +2
In this work, we propose Adversarial Complementary Learning (ACoL) to automatically localize integral objects of semantic interest with weak supervision. We first mathematically pr…
Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification
Qingji Guan, Yaping Huang, Zhun Zhong +3
This paper considers the task of thorax disease classification on chest X-ray images. Existing methods generally use the global image as input for network learning. Such a strategy…