This work investigates dataset vectorization for two dataset-level tasks...
Model calibration usually requires optimizing some parameters (e.g.,
tem...
This work aims to assess how well a model performs under distribution sh...
Generalization and invariance are two essential properties of any machin...
Understanding classifier decision under novel environments is central to...
Motivated by the desire to exploit patterns shared across classes, we pr...
To calculate the model accuracy on a computer vision task, e.g., object
...
Deep domain adaptation methods can reduce the distribution discrepancy b...
This article studies the domain adaptation problem in person
re-identifi...
Person re-identification (re-ID) models trained on one domain often fail...
This paper proposes the SVDNet for retrieval problems, with focus on the...