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Marcos Castro

3 accepted papers

2023

RADIANT: Radar-Image Association Network for 3D Object Detection

AAAI 2023technical

As a direct depth sensor, radar holds promise as a tool to improve monocular 3D object detection, which suffers from depth errors, due in part to the depth-scale ambiguity. On the other hand, leveraging radar depths is hampered by difficulties in precisely associating radar returns with 3D estimates…

2021

Full-Velocity Radar Returns by Radar-Camera Fusion

ICCV 2021poster

A distinctive feature of Doppler radar is the measurement of velocity in the radial direction for radar points. However, the missing tangential velocity component hampers object velocity estimation as well as temporal integration of radar sweeps in dynamic scenes. Recognizing that fusing camera with…

Cited by 28PDFScholar
2021

Radar-Camera Pixel Depth Association for Depth Completion

CVPR 2021poster

While radar and video data can be readily fused at the detection level, fusing them at the pixel level is potentially more beneficial. This is also more challenging in part due to the sparsity of radar, but also because automotive radar beams are much wider than a typical pixel combined with a large…

Cited by 92PDFcodeScholar