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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 11–20 of 187 papers

TitleStatusHype
Training an Open-Vocabulary Monocular 3D Object Detection Model without 3D Data—0
Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object DetectionCode1
MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error PriorsCode2
HeightFormer: A Semantic Alignment Monocular 3D Object Detection Method from Roadside Perspective—0
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection—0
CARLA Drone: Monocular 3D Object Detection from a Different Perspective—0
LAM3D: Leveraging Attention for Monocular 3D Object Detection—0
MonoMM: A Multi-scale Mamba-Enhanced Network for Real-time Monocular 3D Object Detection—0
WARM-3D: A Weakly-Supervised Sim2Real Domain Adaptation Framework for Roadside Monocular 3D Object DetectionCode1
MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object DetectionCode2
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