3 accepted papers
Out-of-distribution (OOD) detection, which aims to determine whether an input is outside the training data distribution or not, is an indispensable task in many computer vision applications. In many of the previous studies on OOD detection for image classification, the class-conditional distribution…
Formula-driven supervised learning (FDSL) is a pre-training method that relies on synthetic images generated from mathematical formulae such as fractals. Prior work on FDSL has shown that pre-training vision transformers on such synthetic datasets can yield competitive accuracy on a wide range of d…
Traffic accident recognition is essential in developing automated driving and Advanced Driving Assistant System technologies. A large dataset of annotated traffic accidents is necessary to improve the accuracy of traffic accident recognition using deep learning models. Conventional traffic accident…