3D Object Detection From Monocular Images
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Benchmarks
Most implemented
Deep Hough Voting for 3D Object Detection in Point Clouds
M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection
SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects
Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild
MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
Papers
SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects
Monocular 3D detectors achieve remarkable performance on cars and smaller objects. However, their performance drops on larger objects, leading to fatal accidents. Some attribute the failures to training data scarcity or …
3D Object Detection3D Object Detection From Monocular ImagesAttributeBEV Segmentation+2Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild
Recognizing scenes and objects in 3D from a single image is a longstanding goal of computer vision with applications in robotics and AR/VR. For 2D recognition, large datasets and scalable solutions have led to unpreceden…
3D Object Detection3D Object Detection From Monocular Images3D Object RecognitionDiversity+3DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection
Modern neural networks use building blocks such as convolutions that are equivariant to arbitrary 2D translations. However, these vanilla blocks are not equivariant to arbitrary 3D translations in the projective manifold…
3D Object Detection3D Object Detection From Monocular ImagesMonocular 3D Object DetectionObject DetectionMonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
Monocular 3D object detection has long been a challenging task in autonomous driving. Most existing methods follow conventional 2D detectors to first localize object centers, and then predict 3D attributes by neighboring…
3D Object Detection3D Object Detection From Monocular ImagesAutonomous DrivingDecoder+4MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
Monocular 3D object detection is an important yet challenging task in autonomous driving. Some existing methods leverage depth information from an off-the-shelf depth estimator to assist 3D detection, but suffer from the…
3D Object Detection3D Object Detection From Monocular ImagesAutonomous DrivingMonocular 3D Object Detection+3ROCA: Robust CAD Model Retrieval and Alignment from a Single Image
We present ROCA, a novel end-to-end approach that retrieves and aligns 3D CAD models from a shape database to a single input image. This enables 3D perception of an observed scene from a 2D RGB observation, characterized…
3D Dense Shape Correspondence3D Object Detection From Monocular Images3D Object Retrieval3D Shape Reconstruction From A Single 2D Image