109 citations · 567 across the 38 of their papers we have counts for
9 papers · 1 filter
Multi-Agent Game Abstraction via Graph Attention Neural Network
Yong Liu, Weixun Wang, Yujing Hu +3
In large-scale multi-agent systems, the large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process…
Differentiable Meta-learning Model for Few-shot Semantic Segmentation
Pinzhuo Tian, Zhangkai Wu, Lei Qi +3
To address the annotation scarcity issue in some cases of semantic segmentation, there have been a few attempts to develop the segmentation model in the few-shot learning paradigm.…
Defensive Few-shot Learning
Wenbin Li, Lei Wang, Xingxing Zhang +4
This paper investigates a new challenging problem called defensive few-shot learning in order to learn a robust few-shot model against adversarial attacks. Simply applying the exis…
Automatic Data Augmentation by Learning the Deterministic Policy
Yinghuan Shi, Tiexin Qin, Yong Liu +3
Aiming to produce sufficient and diverse training samples, data augmentation has been demonstrated for its effectiveness in training deep models. Regarding that the criterion of th…
From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
Weixun Wang, Tianpei Yang, Yong Liu +6
A lot of efforts have been devoted to investigating how agents can learn effectively and achieve coordination in multiagent systems. However, it is still challenging in large-scale…
Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification
Lei Qi, Lei Wang, Jing Huo +2
In this paper, we focus on the semi-supervised person re-identification (Re-ID) case, which only has the intra-camera (within-camera) labels but not inter-camera (cross-camera) lab…
GreyReID: A Two-stream Deep Framework with RGB-grey Information for Person Re-identification
Lei Qi, Lei Wang, Jing Huo +2
In this paper, we observe that most false positive images (i.e., different identities with query images) in the top ranking list usually have the similar color information with the…
Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning
Wenbin Li, Lei Wang, Jinglin Xu +3
Few-shot learning in image classification aims to learn a classifier to classify images when only few training examples are available for each class. Recent work has achieved promi…
A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
Lei Qi, Lei Wang, Jing Huo +3
Unsupervised cross-domain person re-identification (Re-ID) faces two key issues. One is the data distribution discrepancy between source and target domains, and the other is the la…