2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2024
SAM4UDASS: When SAM Meets Unsupervised Domain Adaptive Semantic Segmentation in Intelligent Vehicles
Weihao Yan, Yeqiang Qian, Xingyuan Chen +3
Semantic segmentation plays a critical role in enabling intelligent vehicles to comprehend their surrounding environments. However, deep learning-based methods usually perform poor…
cs.CV2022★ 2 cited
Threshold-adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation
Weihao Yan, Yeqiang Qian, Chunxiang Wang +1
Semantic segmentation is an important task for intelligent vehicles to understand the environment. Current deep learning methods require large amounts of labeled data for training.…
cs.CV2021
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection
Xiaoxiao Yang, Yeqian Qiang, Huijie Zhu +2
Thermal infrared (TIR) image has proven effectiveness in providing temperature cues to the RGB features for multispectral pedestrian detection. Most existing methods directly injec…