Three pillars improving vision foundation model distillation for lidar
Self-supervised image backbones can be used to address complex 2D tasks (eg semantic
segmentation object discovery) very efficiently and with little or no downstream supervision …
segmentation object discovery) very efficiently and with little or no downstream supervision …
An empirical study of training state-of-the-art LiDAR segmentation models
In the rapidly evolving field of autonomous driving, precise segmentation of LiDAR data is
crucial for understanding complex 3D environments. Traditional approaches often rely on …
crucial for understanding complex 3D environments. Traditional approaches often rely on …
Construct to Associate: Cooperative Context Learning for Domain Adaptive Point Cloud Segmentation
G Li - Proceedings of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
This paper tackles the domain adaptation problem in point cloud semantic segmentation
which performs adaptation from a fully labeled domain (source domain) to an unlabeled …
which performs adaptation from a fully labeled domain (source domain) to an unlabeled …
Fusion-then-Distillation: Toward Cross-modal Positive Distillation for Domain Adaptive 3D Semantic Segmentation
In cross-modal unsupervised domain adaptation, a model trained on source-domain data
(eg, synthetic) is adapted to target-domain data (eg, real-world) without access to target …
(eg, synthetic) is adapted to target-domain data (eg, real-world) without access to target …
Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation
We tackle the challenging problem of source-free unsupervised domain adaptation (SFUDA)
for 3D semantic segmentation. It amounts to performing domain adaptation on an unlabeled …
for 3D semantic segmentation. It amounts to performing domain adaptation on an unlabeled …
UniDSeg: Unified Cross-Domain 3D Semantic Segmentation via Visual Foundation Models Prior
3D semantic segmentation using an adapting model trained from a source domain with or
without accessing unlabeled target-domain data is the fundamental task in computer vision …
without accessing unlabeled target-domain data is the fundamental task in computer vision …