Annotator: A generic active learning baseline for lidar semantic segmentation

B Xie, S Li, Q Guo, C Liu… - Advances in Neural …, 2023 - proceedings.neurips.cc
Active learning, a label-efficient paradigm, empowers models to interactively query an oracle
for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem …
被引用次数：11 相关文章

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

B Xie, S Li, Q Guo, CH Liu, X Cheng - arXiv preprint arXiv:2310.20293, 2023 - arxiv.org
Active learning, a label-efficient paradigm, empowers models to interactively query an oracle
for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem …

Annotator a generic active learning baseline for LiDAR semantic segmentation

B Xie, S Li, Q Guo, CH Liu, X Cheng - Proceedings of the 37th …, 2023 - dl.acm.org
Active learning, a label-efficient paradigm, empowers models to interactively query an oracle
for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem …

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

B Xie, S Li, CH Liu, X Cheng - Thirty-seventh Conference on Neural … - openreview.net
Active learning, a label-efficient paradigm, empowers models to interactively query an oracle
for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem …

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

B Xie, S Li, Q Guo, CH Liu, X Cheng - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Active learning, a label-efficient paradigm, empowers models to interactively query an oracle
for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem …