1k citations · 1.1k across the 14 of their papers we have counts for
17 papers
Large-scale Training Data Search for Object Re-identification
Yue Yao, Huan Lei, Tom Gedeon +1
We consider a scenario where we have access to the target domain, but cannot afford on-the-fly training data annotation, and instead would like to construct an alternative training…
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…
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…
Learning to Select Camera Views: Efficient Multiview Understanding at Few Glances
Yunzhong Hou, Stephen Gould, Liang Zheng
Multiview camera setups have proven useful in many computer vision applications for reducing ambiguities, mitigating occlusions, and increasing field-of-view coverage. However, the…
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…
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…