Label-efficient and reliable semantic segmentation is essential for many...
Test-time adaptation (TTA) intends to adapt the pretrained model to test...
Generalizing models trained on normal visual conditions to target domain...
We launch EVA, a vision-centric foundation model to explore the limits o...
Domain adaptive semantic segmentation attempts to make satisfactory dens...
Unsupervised domain adaptation has recently emerged as an effective para...
Self-training has greatly facilitated domain adaptive semantic segmentat...
Although there is significant progress in supervised semantic segmentati...
Domain adaptive semantic segmentation refers to making predictions on a
...
Domain Adaptation (DA) attempts to transfer knowledge learned in the lab...
Unsupervised domain adaptation challenges the problem of transferring
kn...
Heterogeneous domain adaptation (HDA) transfers knowledge across source ...
Tremendous research efforts have been made to thrive deep domain adaptat...