3d object detection from images for autonomous driving: a survey
3D object detection from images, one of the fundamental and challenging problems in
autonomous driving, has received increasing attention from both industry and academia in …
autonomous driving, has received increasing attention from both industry and academia in …
Is pseudo-lidar needed for monocular 3d object detection?
Recent progress in 3D object detection from single images leverages monocular depth
estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors …
estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors …
Delving into localization errors for monocular 3d object detection
Estimating 3D bounding boxes from monocular images is an essential component in
autonomous driving, while accurate 3D object detection from this kind of data is very …
autonomous driving, while accurate 3D object detection from this kind of data is very …
Imvoxelnet: Image to voxels projection for monocular and multi-view general-purpose 3d object detection
In this paper, we introduce the task of multi-view RGB-based 3D object detection as an end-
to-end optimization problem. To address this problem, we propose ImVoxelNet, a novel fully …
to-end optimization problem. To address this problem, we propose ImVoxelNet, a novel fully …
Deviant: Depth equivariant network for monocular 3d object detection
Modern neural networks use building blocks such as convolutions that are equivariant to
arbitrary 2 D translations. However, these vanilla blocks are not equivariant to arbitrary 3 D …
arbitrary 2 D translations. However, these vanilla blocks are not equivariant to arbitrary 3 D …
Ground-aware monocular 3d object detection for autonomous driving
Estimating the 3D position and orientation of objects in the environment with a single RGB
camera is a critical and challenging task for low-cost urban autonomous driving and mobile …
camera is a critical and challenging task for low-cost urban autonomous driving and mobile …
Groomed-nms: Grouped mathematically differentiable nms for monocular 3d object detection
Modern 3D object detectors have immensely benefited from the end-to-end learning idea.
However, most of them use a post-processing algorithm called Non-Maximal Suppression …
However, most of them use a post-processing algorithm called Non-Maximal Suppression …
CAMRL: A joint method of channel attention and multidimensional regression loss for 3D object detection in automated vehicles
H Gao, D Fang, J ** perception methods
on ego-vehicle sensors, people tend to overlook an alternative approach to leverage …
on ego-vehicle sensors, people tend to overlook an alternative approach to leverage …