OOD-CV challenge is an out-of-distribution generalization task. To solve...
OOD-CV challenge is an out-of-distribution generalization task. In this
...
Convolutional neural networks (CNNs) have demonstrated gratifying result...
Vanilla unsupervised domain adaptation methods tend to optimize the mode...
Semi-supervised object detection has made significant progress with the
...
Self-training for unsupervised domain adaptive object detection is a
cha...
Inspired by the remarkable zero-shot generalization capacity of
vision-l...
Convolutional neural networks (CNNs) have achieved significant success i...
Domain generalization (DG) is a fundamental yet very challenging researc...
Conventional domain generalization aims to learn domain invariant
repres...
Nowadays advanced image editing tools and technical skills produce tampe...
It is a strong prerequisite to access source data freely in many existin...
False positive is one of the most serious problems brought by agnostic d...
Unsupervised domain adaptation (UDA) assumes that source and target doma...
Deep clustering against self-supervised learning is a very important and...
Audio classification can distinguish different kinds of sounds, which is...
Deep region-based object detector consists of a region proposal step and...