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3D Object Detection From Monocular Images
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This is the task of detecting 3D objects from monocular images (as opposed to LiDAR based counterparts). It is usually associated with autonomous driving based tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Orthographic Feature Transform for Monocular 3D Object Detection )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection
MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
ROCA: Robust CAD Model Retrieval and Alignment from a Single Image
Geometry Uncertainty Projection Network for Monocular 3D Object Detection
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection
Delving into Localization Errors for Monocular 3D Object Detection
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection
CubifAE-3D: Monocular Camera Space Cubification for Auto-Encoder based 3D Object Detection
M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
Disentangling Monocular 3D Object Detection
Deep Hough Voting for 3D Object Detection in Point Clouds
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles
Orthographic Feature Transform for Monocular 3D Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.