Robust point cloud parsing under all-weather conditions is crucial to le...
LiDAR point clouds, which are usually scanned by rotating LiDAR sensors
...
Video semantic segmentation has achieved great progress under the superv...
Semi-supervised semantic segmentation learns from small amounts of label...
Point cloud data have been widely explored due to its superior accuracy ...
Unsupervised domain adaptation aims to align a labeled source domain and...
Video semantic segmentation is an essential task for the analysis and
un...
Transfer learning from synthetic to real data has been proved an effecti...
Instance contrast for unsupervised representation learning has achieved ...
Unsupervised domain adaptation (UDA) involves a supervised loss in a lab...
Contemporary domain adaptive semantic segmentation aims to address data
...
Recent progresses in domain adaptive semantic segmentation demonstrate t...
Panoptic segmentation unifies semantic segmentation and instance segment...
Domain generalization aims to learn a generalizable model from a known s...
Scene understanding based on LiDAR point cloud is an essential task for
...
Unsupervised domain adaptive object detection aims to adapt detectors fr...
Multimodal information (e.g., visible and thermal) can generate robust
p...
Effective fusion of complementary information captured by multi-modal se...
Multispectral pedestrian detection has received extensive attention in r...