activity
20192023
most citedA Unified Model for Multi-class Anomaly Detection

87 citations · 110 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 2 cited

STRAP: Structured Object Affordance Segmentation with Point Supervision

Leiyao Cui, Xiaoxue Chen, Hao Zhao +2

With significant annotation savings, point supervision has been proven effective for numerous 2D and 3D scene understanding problems. This success is primarily attributed to the st…

cs.CV2022

Neighbor Regularized Bayesian Optimization for Hyperparameter Optimization

Lei Cui, Yangguang Li, Xin Lu +2

Bayesian Optimization (BO) is a common solution to search optimal hyperparameters based on sample observations of a machine learning model. Existing BO algorithms could converge sl…

cs.CV2022★ 2 cited

ADTR: Anomaly Detection Transformer with Feature Reconstruction

Zhiyuan You, Kai Yang, Wenhan Luo +3

Anomaly detection with only prior knowledge from normal samples attracts more attention because of the lack of anomaly samples. Existing CNN-based pixel reconstruction approaches s…

cs.CV2022★ 87 cited

A Unified Model for Multi-class Anomaly Detection

Zhiyuan You, Lei Cui, Yujun Shen +4

Despite the rapid advance of unsupervised anomaly detection, existing methods require to train separate models for different objects. In this work, we present UniAD that accomplish…

cs.CV2022

Few-shot Object Counting with Similarity-Aware Feature Enhancement

Zhiyuan You, Kai Yang, Wenhan Luo +3

This work studies the problem of few-shot object counting, which counts the number of exemplar objects (i.e., described by one or several support images) occurring in the query ima…

cs.CV2021★ 3 cited

AutoSampling: Search for Effective Data Sampling Schedules

Ming Sun, Haoxuan Dou, Baopu Li +3

Data sampling acts as a pivotal role in training deep learning models. However, an effective sampling schedule is difficult to learn due to the inherently high dimension of paramet…