Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey
The 3D point cloud (3DPC) has significantly evolved and benefited from the advance of
deep learning (DL). However, the latter faces various issues, including the lack of data or …
deep learning (DL). However, the latter faces various issues, including the lack of data or …
Dg-pic: Domain generalized point-in-context learning for point cloud understanding
Recent point cloud understanding research suffers from performance drops on unseen data,
due to the distribution shifts across different domains. While recent studies use Domain …
due to the distribution shifts across different domains. While recent studies use Domain …
A survey of label-efficient deep learning for 3D point clouds
In the past decade, deep neural networks have achieved significant progress in point cloud
learning. However, collecting large-scale precisely-annotated point clouds is extremely …
learning. However, collecting large-scale precisely-annotated point clouds is extremely …
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
The emergence of Multi-Camera 3D Object Detection (MC3D-Det), facilitated by bird's-eye
view (BEV) representation, signifies a notable progression in 3D object detection. Scaling …
view (BEV) representation, signifies a notable progression in 3D object detection. Scaling …
DaF-BEVSeg: Distortion-aware Fisheye Camera based Bird's Eye View Segmentation with Occlusion Reasoning
Semantic segmentation is an effective way to perform scene understanding. Recently,
segmentation in 3D Bird's Eye View (BEV) space has become popular as its directly used by …
segmentation in 3D Bird's Eye View (BEV) space has become popular as its directly used by …
OccRWKV: Rethinking Efficient 3D Semantic Occupancy Prediction with Linear Complexity
3D semantic occupancy prediction networks have demonstrated remarkable capabilities in
reconstructing the geometric and semantic structure of 3D scenes, providing crucial …
reconstructing the geometric and semantic structure of 3D scenes, providing crucial …
Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains
In the realm of LiDAR-based perception, significant strides have been made, yet domain
generalization remains a substantial challenge. The performance often deteriorates when …
generalization remains a substantial challenge. The performance often deteriorates when …
Instance-wise Domain Generalization for Cross-scene Wetland Classification with Hyperspectral and LiDAR Data
F Guo, Z Li, G Ren, L Wang, J Zhang… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Wetland is one of the three ecosystems in the world, and collaborative monitoring using
hyperspectral images (HSIs) and light detection and ranging (LiDAR) has been important for …
hyperspectral images (HSIs) and light detection and ranging (LiDAR) has been important for …
Hierarchical Context Alignment with Disentangled Geometric and Temporal Modeling for Semantic Occupancy Prediction
Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding
complex 3D scenes from limited 2D image observations. Existing SOP methods typically …
complex 3D scenes from limited 2D image observations. Existing SOP methods typically …
Density-aware Domain Generalization for LiDAR Semantic Segmentation
3D LiDAR-based perception has made remarkable advancements, leading to the
widespread adoption of LiDAR in autonomous driving systems. Despite these technological …
widespread adoption of LiDAR in autonomous driving systems. Despite these technological …