activity
20162022
most citedRotation Transformation Network: Learning View-Invariant Point Cloud for Classification and Segmentation

5 citations · 11 across the 8 of their papers we have counts for

collaborators

14 papers

cs.CV2022

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…

cs.CV2022

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…

cs.CV20221 cited

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…

cs.CV20215 cited

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…

cs.CV20215 cited

Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning

Liu Bo, Qiulei Dong, Zhanyi Hu

Transductive zero-shot learning (T-ZSL) which could alleviate the domain shift problem in existing ZSL works, has received much attention recently. However, an open problem in T-ZS…

cs.RO2020

Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements

Jinxu Liu, Wei Gao, Zhanyi Hu

Unlike loose coupling approaches and the EKF-based approaches in the literature, we propose an optimization-based visual-inertial SLAM tightly coupled with raw Global Navigation Sa…