Liujuan Cao

Learning Similarity-specific Dictionary for Zero-shot Fine-grained Recognition

2019

In this paper, we study the problem of zero-shot fine-grained recognition. It aims to distinguish unseen subordinate categories through some other seen categories within an entry-level category. We demonstrate the necessity to learn multiple latent …

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

2021 · arXiv (Cornell University)

A resource-adaptive supernet adjusts its subnets for inference to fit the dynamically available resources. In this paper, we propose prioritized subnet sampling to train a resource-adaptive supernet, termed PSS-Net. We maintain multiple subnet pools, each …

Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection

2024 · arXiv (Cornell University)

Due to the scarcity and unpredictable nature of defect samples, industrial anomaly detection (IAD) predominantly employs unsupervised learning. However, all unsupervised IAD methods face a common challenge: the inherent bias in normal samples, which causes …