Adapting Object Detectors via Selective Cross-Domain Alignment

CVPR 2019 Xinge Zhu Jiangmiao Pang Ceyuan Yang Jianping Shi Dahua Lin

State-of-the-art object detectors are usually trained on public datasets. They often face substantial difficulties when applied to a different domain, where the imaging condition differs significantly and the corresponding annotated data are unavailable (or expensive to acquire)... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Unsupervised Domain Adaptation Cityscapes to Foggy Cityscapes SCDA [email protected] 33.8 # 3