18 citations · 22 across the 6 of their papers we have counts for
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cs.CV2024
Back2Color: Domain-Adaptive Synthetic-to-Real Monocular Depth Estimation for Dynamic Traffic Scenes
Yufan Zhu, Chongzhi Ran, Mingtao Feng +3
Accurate monocular depth estimation is a fundamental component of vision-based perception systems in intelligent transportation applications. Despite recent progress, unsupervised…
cs.CV2024
UDA4Inst: Unsupervised Domain Adaptation for Instance Segmentation
Yachan Guo, Yi Xiao, Danna Xue +2
Instance segmentation is crucial for autonomous driving, but is hindered by the lack of annotated real-world data due to expensive labeling costs. Unsupervised Domain Adaptation (U…
cs.CV2024★ 3 cited
Guiding Attention in End-to-End Driving Models
Diego Porres, Yi Xiao, Gabriel Villalonga +2
Vision-based end-to-end driving models trained by imitation learning can lead to affordable solutions for autonomous driving. However, training these well-performing models usually…