5 citations · 6 across the 5 of their papers we have counts for
5 papers
An Iterative Co-Training Transductive Framework for Zero Shot Learning
Bo Liu, Lihua Hu, Qiulei Dong +1
In zero-shot learning (ZSL) community, it is generally recognized that transductive learning performs better than inductive one as the unseen-class samples are also used in its tra…
Semantic-diversity transfer network for generalized zero-shot learning via inner disagreement based OOD detector
Bo Liu, Qiulei Dong, Zhanyi Hu
Zero-shot learning (ZSL) aims to recognize objects from unseen classes, where the kernel problem is to transfer knowledge from seen classes to unseen classes by establishing approp…
HardBoost: Boosting Zero-Shot Learning with Hard Classes
Bo Liu, Lihua Hu, Zhanyi Hu +1
This work is a systematical analysis on the so-called hard class problem in zero-shot learning (ZSL), that is, some unseen classes disproportionally affect the ZSL performances tha…
Rotation Transformation Network: Learning View-Invariant Point Cloud for Classification and Segmentation
Shuang Deng, Bo Liu, Qiulei Dong +1
Many recent works show that a spatial manipulation module could boost the performances of deep neural networks (DNNs) for 3D point cloud analysis. In this paper, we aim to provide…
Zero-Shot Learning from Adversarial Feature Residual to Compact Visual Feature
Bo Liu, Qiulei Dong, Zhanyi Hu
Recently, many zero-shot learning (ZSL) methods focused on learning discriminative object features in an embedding feature space, however, the distributions of the unseen-class fea…