17 citations · 19 across the 3 of their papers we have counts for
7 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…
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…
To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions
Junjie Zhang, Lingqiao Liu, Peng Wang +1
Real-world visual data often exhibits a long-tailed distribution, where some ''head'' classes have a large number of samples, yet only a few samples are available for ''tail'' clas…
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…
Compare More Nuanced:Pairwise Alignment Bilinear Network For Few-shot Fine-grained Learning
Huaxi Huang, Junjie Zhang, Jian Zhang +2
The recognition ability of human beings is developed in a progressive way. Usually, children learn to discriminate various objects from coarse to fine-grained with limited supervis…
Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards
Junjie Zhang, Qi Wu, Chunhua Shen +3
Despite significant progress in a variety of vision-and-language problems, developing a method capable of asking intelligent, goal-oriented questions about images is proven to be a…