activity
20212023
most citedPositive Sample Propagation along the Audio-Visual Event Line

6 citations · 23 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2023★ 1 cited

Training with Product Digital Twins for AutoRetail Checkout

Yue Yao, Xinyu Tian, Zheng Tang +4

Automating the checkout process is important in smart retail, where users effortlessly pass products by hand through a camera, triggering automatic product detection, tracking, and…

cs.CV2023

The 7th AI City Challenge

Milind Naphade, Shuo Wang, David C. Anastasiu +17

The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems…

cs.CV2023★ 3 cited

A Bag-of-Prototypes Representation for Dataset-Level Applications

Weijie Tu, Weijian Deng, Tom Gedeon +1

This work investigates dataset vectorization for two dataset-level tasks: assessing training set suitability and test set difficulty. The former measures how suitable a training se…

cs.CV2023★ 3 cited

Unsupervised Evaluation of Out-of-distribution Detection: A Data-centric Perspective

Yuhang Zhang, Weihong Deng, Liang Zheng

Out-of-distribution (OOD) detection methods assume that they have test ground truths, i.e., whether individual test samples are in-distribution (IND) or OOD. However, in the real w…

cs.LG2023

Adaptive Calibrator Ensemble for Model Calibration under Distribution Shift

Yuli Zou, Weijian Deng, Liang Zheng

Model calibration usually requires optimizing some parameters (e.g., temperature) w.r.t an objective function (e.g., negative log-likelihood). In this paper, we report a plain, imp…

cs.LG2023★ 1 cited

Confidence and Dispersity Speak: Characterising Prediction Matrix for Unsupervised Accuracy Estimation

Weijian Deng, Yumin Suh, Stephen Gould +1

This work aims to assess how well a model performs under distribution shifts without using labels. While recent methods study prediction confidence, this work reports prediction di…