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3d-cvf icon 3d-cvf

[ECCV 2020] This is the official implementation of 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection

bevfusion icon bevfusion

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

clocs icon clocs

CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection

cmflow icon cmflow

[CVPR 2023 Highlight] Hidden Gems: 4D Radar Scene Flow Learning Using Cross-Modal Supervision

cmt icon cmt

[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

copilot icon copilot

Lane and obstacle detection for active assistance during driving. Uses windowed sweep for lane detection. Combination of object tracking and YOLO for obstacles. Determines lane change, relative velocity and time to collision

crn icon crn

[ICCV'23] Official implementation of CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception

deepfusionmot icon deepfusionmot

Code for RA-L journal and IROS 2022 paper "DeepFusionMOT: A 3D Multi-Object Tracking Framework Based on Camera-LiDAR Fusion with Deep Association".

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

delamain icon delamain

Self driving car project for Harvard Extension School Robotic Class DGMD E-17 (26008) Spring 2021

detr icon detr

End-to-End Object Detection with Transformers

dorn_radar icon dorn_radar

Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression Network

eagermot icon eagermot

Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

fucking-algorithm icon fucking-algorithm

刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.

futr3d icon futr3d

Code for paper: FUTR3D: a unified sensor fusion framework for 3d detection

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