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Monocular 3D Object Detection

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.

Papers

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Showing 91–100 of 187 papers

TitleStatusHype
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object DetectionCode1
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes—0
MonoGround: Detecting Monocular 3D Objects from the GroundCode1
Delving into the Pre-training Paradigm of Monocular 3D Object Detection—0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving—0
Towards Model Generalization for Monocular 3D Object Detection—0
Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection—0
Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training—0
Shape-Aware Monocular 3D Object Detection—0
Homography Loss for Monocular 3D Object DetectionCode1
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