9 citations · 26 across the 9 of their papers we have counts for
10 papers · 1 filter
PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning
Huaxi Huang, Junjie Zhang, Jian Zhang +2
The predicament in semi-supervised few-shot learning (SSFSL) is to maximize the value of the extra unlabeled data to boost the few-shot learner. In this paper, we propose a Poisson…
Multi-layer Feature Aggregation for Deep Scene Parsing Models
Litao Yu, Yongsheng Gao, Jun Zhou +2
Scene parsing from images is a fundamental yet challenging problem in visual content understanding. In this dense prediction task, the parsing model assigns every pixel to a catego…
Dual Attention on Pyramid Feature Maps for Image Captioning
Litao Yu, Jian Zhang, Qiang Wu
Generating natural sentences from images is a fundamental learning task for visual-semantic understanding in multimedia. In this paper, we propose to apply dual attention on pyrami…
TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples
Huaxi Huang, Junjie Zhang, Jian Zhang +2
The challenges of high intra-class variance yet low inter-class fluctuations in fine-grained visual categorization are more severe with few labeled samples, \textit{i.e.,} Fine-Gra…
SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification
Yan Huang, Qiang Wu, JingSong Xu +1
Cross-domain person re-identification (re-ID) is challenging due to the bias between training and testing domains. We observe that if backgrounds in the training and testing datase…
Low-Rank Pairwise Alignment Bilinear Network For Few-Shot Fine-Grained Image Classification
Huaxi Huang, Junjie Zhang, Jian Zhang +2
Deep neural networks have demonstrated advanced abilities on various visual classification tasks, which heavily rely on the large-scale training samples with annotated ground-truth…