activity
20192021
most citedFew-Shot Open-Set Recognition using Meta-Learning

5 citations · 9 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Semi-supervised Long-tailed Recognition using Alternate Sampling

Bo Liu, Haoxiang Li, Hao Kang +2

Main challenges in long-tailed recognition come from the imbalanced data distribution and sample scarcity in its tail classes. While techniques have been proposed to achieve a more…

cs.CV2021

GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition

Bo Liu, Haoxiang Li, Hao Kang +2

The problem of long-tailed recognition, where the number of examples per class is highly unbalanced, is considered. It is hypothesized that the well known tendency of standard clas…

cs.CV2021

Breadcrumbs: Adversarial Class-Balanced Sampling for Long-tailed Recognition

Bo Liu, Haoxiang Li, Hao Kang +2

The problem of long-tailed recognition, where the number of examples per class is highly unbalanced, is considered. While training with class-balanced sampling has been shown effec…

cs.CV20211 cited

Beyond Visual Attractiveness: Physically Plausible Single Image HDR Reconstruction for Spherical Panoramas

Wei Wei, Li Guan, Yue Liu +4

HDR reconstruction is an important task in computer vision with many industrial needs. The traditional approaches merge multiple exposure shots to generate HDRs that correspond to…

cs.CV20205 cited

Few-Shot Open-Set Recognition using Meta-Learning

Bo Liu, Hao Kang, Haoxiang Li +2

The problem of open-set recognition is considered. While previous approaches only consider this problem in the context of large-scale classifier training, we seek a unified solutio…

cs.RO20193 cited

LeRoP: A Learning-Based Modular Robot Photography Framework

Hao Kang, Jianming Zhang, Haoxiang Li +3

We introduce a novel framework for automatic capturing of human portraits. The framework allows the robot to follow a person to the desired location using a Person Re-identificatio…