Vista: Boosting 3d object detection via dual cross-view spatial attention
Detecting objects from LiDAR point clouds is of tremendous significance in autonomous
driving. In spite of good progress, accurate and reliable 3D detection is yet to be achieved …
driving. In spite of good progress, accurate and reliable 3D detection is yet to be achieved …
Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection
Lidars and cameras are critical sensors that provide complementary information for 3D
detection in autonomous driving. While prevalent multi-modal methods simply decorate raw …
detection in autonomous driving. While prevalent multi-modal methods simply decorate raw …
SIENet: Spatial information enhancement network for 3D object detection from point cloud
LiDAR-based 3D object detection pushes forward an immense influence on autonomous
vehicles. Due to the limitation of the intrinsic properties of LiDAR, fewer points are collected …
vehicles. Due to the limitation of the intrinsic properties of LiDAR, fewer points are collected …
SupFusion: Supervised LiDAR-camera fusion for 3D object detection
LiDAR-Camera fusion-based 3D detection is a critical task for automatic driving. In recent
years, many LiDAR-Camera fusion approaches sprung up and gained promising …
years, many LiDAR-Camera fusion approaches sprung up and gained promising …
RoIFusion: 3D object detection from LiDAR and vision
C Chen, LZ Fragonara, A Tsourdos - IEEE Access, 2021 - ieeexplore.ieee.org
When localizing and detecting 3D objects for autonomous driving scenes, obtaining
information from multiple sensors (eg, camera, LIDAR) is capable of mutually offering useful …
information from multiple sensors (eg, camera, LIDAR) is capable of mutually offering useful …
Mlcvnet: Multi-level context votenet for 3d object detection
In this paper, we address the 3D object detection task by capturing multi-level contextual
information with the self-attention mechanism and multi-scale feature fusion. Most existing …
information with the self-attention mechanism and multi-scale feature fusion. Most existing …
Pointaugmenting: Cross-modal augmentation for 3d object detection
Camera and LiDAR are two complementary sensors for 3D object detection in the
autonomous driving context. Camera provides rich texture and color cues while LiDAR …
autonomous driving context. Camera provides rich texture and color cues while LiDAR …
Pvgnet: A bottom-up one-stage 3d object detector with integrated multi-level features
Quantization-based methods are widely used in LiDAR points 3D object detection for its
efficiency in extracting context information. Unlike image where the context information is …
efficiency in extracting context information. Unlike image where the context information is …
Logonet: Towards accurate 3d object detection with local-to-global cross-modal fusion
LiDAR-camera fusion methods have shown impressive performance in 3D object detection.
Recent advanced multi-modal methods mainly perform global fusion, where image features …
Recent advanced multi-modal methods mainly perform global fusion, where image features …
Spatial information enhancement network for 3D object detection from point cloud
LiDAR-based 3D object detection pushes forward an immense influence on autonomous
vehicles. Due to the limitation of the intrinsic properties of LiDAR, fewer points are collected …
vehicles. Due to the limitation of the intrinsic properties of LiDAR, fewer points are collected …