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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 176–187 of 187 papers

TitleStatusHype
Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems—0
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes—0
Shape-Aware Monocular 3D Object Detection—0
Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints—0
Towards Generalization Across Depth for Monocular 3D Object Detection—0
SpikeSMOKE: Spiking Neural Networks for Monocular 3D Object Detection with Cross-Scale Gated Coding—0
The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection—0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving—0
Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection—0
Towards Model Generalization for Monocular 3D Object Detection—0
Training an Open-Vocabulary Monocular 3D Object Detection Model without 3D Data—0
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection—0
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