Frustumformer: Adaptive instance-aware resampling for multi-view 3d detection
The transformation of features from 2D perspective space to 3D space is essential to multi-
view 3D object detection. Recent approaches mainly focus on the design of view …
view 3D object detection. Recent approaches mainly focus on the design of view …
Svqnet: Sparse voxel-adjacent query network for 4d spatio-temporal lidar semantic segmentation
LiDAR-based semantic perception tasks are critical yet challenging for autonomous driving.
Due to the motion of objects and static/dynamic occlusion, temporal information plays an …
Due to the motion of objects and static/dynamic occlusion, temporal information plays an …
A survey of robust 3d object detection methods in point clouds
The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection
methods, datasets, and challenges. We describe novel data augmentation methods …
methods, datasets, and challenges. We describe novel data augmentation methods …
3d object detection with multi-frame rgb-lidar feature alignment
Single-frame 3D detection is a well-studied vision problem with dedicated benchmarks and
a large body of work. This knowledge has translated to a myriad of real-world applications …
a large body of work. This knowledge has translated to a myriad of real-world applications …
Incorporating Spatio-Temporal Information in Frustum-ConvNet for Improved 3D Object Detection in Instrumented Vehicles
GM Venkatesh, NE O'Connor… - 2022 10th European …, 2022 - ieeexplore.ieee.org
Environmental perception is a key task for autonomous vehicles to ensure intelligent
planning and safe decision-making. Most current state-of-the-art perceptual methods in …
planning and safe decision-making. Most current state-of-the-art perceptual methods in …
Multimodal spatio-temporal deep learning framework for 3D object detection in instrumented vehicles
VG Munirathnam - 2023 - doras.dcu.ie
This thesis presents the utilization of multiple modalities, such as image and lidar, to
incorporate spatio-temporal information from sequence data into deep learning architectures …
incorporate spatio-temporal information from sequence data into deep learning architectures …
A Survey of Robust LiDAR-based 3D Object Detection Methods for Autonomous Driving
The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection
methods, datasets, and challenges. We describe novel data augmentation methods …
methods, datasets, and challenges. We describe novel data augmentation methods …