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Found 6 papers, 0 papers with code
Analyze the Robustness of Classifiers under Label Noise
This study explores the robustness of label noise classifiers, aiming to enhance model resilience against noisy data in complex real-world scenarios.
Analyze the robustness of three NMF algorithms (Robust NMF with L1 norm, L2-1 norm NMF, L2 NMF)
Non-negative matrix factorization (NMF) and its variants have been widely employed in clustering and classification tasks (Long, & Jian , 2021).
AOP-Net: All-in-One Perception Network for Joint LiDAR-based 3D Object Detection and Panoptic Segmentation
In this method, a dual-task 3D backbone is developed to extract both panoptic- and detection-level features from the input LiDAR point cloud.
A Versatile Multi-View Framework for LiDAR-based 3D Object Detection with Guidance from Panoptic Segmentation
In our method, the 3D object detection backbone in Bird's-Eye-View (BEV) plane is augmented by the injection of Range-View (RV) feature maps from the 3D panoptic segmentation backbone.
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds
A fast and accurate panoptic segmentation system for LiDAR point clouds is crucial for autonomous driving vehicles to understand the surrounding objects and scenes.
SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering
Thus, we propose to use a novel centroid-aware repel loss as an additional term to effectively supervise the network to differentiate each object cluster with its neighbours.
