56 citations · 221 across the 25 of their papers we have counts for
4 papers · 1 filter
Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud
Yachao Zhang, Zonghao Li, Yuan Xie +3
Existing methods for large-scale point cloud semantic segmentation require expensive, tedious and error-prone manual point-wise annotations. Intuitively, weakly supervised training…
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
Tianfang Sun, Zhizhong Zhang, Xin Tan +3
Weakly supervised point cloud semantic segmentation methods that require 1\% or fewer labels, hoping to realize almost the same performance as fully supervised approaches, which re…
Variational Distillation for Multi-View Learning
Xudong Tian, Zhizhong Zhang, Cong Wang +6
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions. Howev…
Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting
Jiaqi Gao, Jingqi Li, Hongming Shan +4
Crowd counting has important applications in public safety and pandemic control. A robust and practical crowd counting system has to be capable of continuously learning with the ne…