1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2023
LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation
Amirreza Shaban, JoonHo Lee, Sanghun Jung +2
We introduce LiDAR-UDA, a novel two-stage self-training-based Unsupervised Domain Adaptation (UDA) method for LiDAR segmentation. Existing self-training methods use a model trained…
cs.CV2023
Unsupervised Accuracy Estimation of Deep Visual Models using Domain-Adaptive Adversarial Perturbation without Source Samples
JoonHo Lee, Jae Oh Woo, Hankyu Moon +1
Deploying deep visual models can lead to performance drops due to the discrepancies between source and target distributions. Several approaches leverage labeled source data to esti…
cs.RO2023★ 1 cited
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
Xiangyun Meng, Nathan Hatch, Alexander Lambert +11
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structure…