Monocular 3D Object Detection
76 papers with code • 15 benchmarks • 5 datasets
Monocular 3D Object Detection is the task to draw 3D bounding box around objects in a single 2D RGB image. It is localization task but without any extra information like depth or other sensors or multiple-images.
Benchmarks
These leaderboards are used to track progress in Monocular 3D Object Detection
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Libraries
Use these libraries to find Monocular 3D Object Detection models and implementations
KITTI
SUN RGB-D
Virtual KITTI
OPV2V
Virtual KITTI 2
Most implemented papers
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection
It presents the MonoCon method which learns Monocular Contexts, as auxiliary tasks in training, to help monocular 3D object detection.
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection
As a result, DEVIANT is equivariant to the depth translations in the projective manifold whereas vanilla networks are not.
Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps
mediabrain-sjtu/where2comm
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Where2comm has two distinct advantages: i) it considers pragmatic compression and uses less communication to achieve higher perception performance by focusing on perceptually critical areas; and ii) it can handle varying communication bandwidth by dynamically adjusting spatial areas involved in communication.
Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image
We propose a computational framework to jointly parse a single RGB image and reconstruct a holistic 3D configuration composed by a set of CAD models using a stochastic grammar model.
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation
Holistic 3D indoor scene understanding refers to jointly recovering the i) object bounding boxes, ii) room layout, and iii) camera pose, all in 3D.
Orthographic Feature Transform for Monocular 3D Object Detection
tom-roddick/oft
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This allows us to reason holistically about the spatial configuration of the scene in a domain where scale is consistent and distances between objects are meaningful.
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization
We propose MonoGRNet for the amodal 3D object detection from a monocular RGB image via geometric reasoning in both the observed 2D projection and the unobserved depth dimension.
Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud
Following the pipeline of two-stage 3D detection algorithms, we detect 2D object proposals in the input image and extract a point cloud frustum from the pseudo-LiDAR for each proposal.
Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction
We present MonoPSR, a monocular 3D object detection method that leverages proposals and shape reconstruction.
Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image
yinyunie/Total3DUnderstanding
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CVPR 2020
Semantic reconstruction of indoor scenes refers to both scene understanding and object reconstruction.
