241 citations · 279 across the 4 of their papers we have counts for
12 papers
Learning Open Set Network with Discriminative Reciprocal Points
Guangyao Chen, Limeng Qiao, Yemin Shi +5
Open set recognition is an emerging research area that aims to simultaneously classify samples from predefined classes and identify the rest as 'unknown'. In this process, one of t…
Cooperative Bi-path Metric for Few-shot Learning
Zeyuan Wang, Yifan Zhao, Jia Li +1
Given base classes with sufficient labeled samples, the target of few-shot classification is to recognize unlabeled samples of novel classes with only a few labeled samples. Most e…
Is Depth Really Necessary for Salient Object Detection?
Jiawei Zhao, Yifan Zhao, Jia Li +1
Salient object detection (SOD) is a crucial and preliminary task for many computer vision applications, which have made progress with deep CNNs. Most of the existing methods mainly…
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning
Limeng Qiao, Yemin Shi, Jia Li +3
Few-shot learning, which aims at extracting new concepts rapidly from extremely few examples of novel classes, has been featured into the meta-learning paradigm recently. Yet, the…
Exploring Reciprocal Attention for Salient Object Detection by Cooperative Learning
Changqun Xia, Jia Li, Jinming Su +1
Typically, objects with the same semantics are not always prominent in images containing different backgrounds. Motivated by this observation that accurately salient object detecti…
Learning Local Feature Descriptor with Motion Attribute for Vision-based Localization
Yafei Song, Di Zhu, Jia Li +2
In recent years, camera-based localization has been widely used for robotic applications, and most proposed algorithms rely on local features extracted from recorded images. For be…