2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CV2024
Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation
Chuandong Liu, Xingxing Weng, Shuguo Jiang +3
This paper explores scene affinity (AIScene), namely intra-scene consistency and inter-scene correlation, for semi-supervised LiDAR semantic segmentation in driving scenes. Adoptin…
cs.CV2024
Are Dense Labels Always Necessary for 3D Object Detection from Point Cloud?
Chenqiang Gao, Chuandong Liu, Jun Shu +5
Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training. However, collecting such large-scale densely-s…
cs.CV2023★ 2 cited
Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection
Chuandong Liu, Chenqiang Gao, Fangcen Liu +3
State-of-the-art 3D object detectors are usually trained on large-scale datasets with high-quality 3D annotations. However, such 3D annotations are often expensive and time-consumi…