以下均是一些常用的基线模型,方便日后使用做一些整理
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2nd of AI City Challenge 2018 code paper
title:Vehicle Re-Identification with the Space-Time Prior -
A two-stream multitask learning network) to do vehicle Re-identification, vehicle search code
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A baseline report by VeRi code
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A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras code paper
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A baseline using triplet loss and crossentropy loss code
vehicle re
车辆再识别(重识别)技术综述及代码实践

本文整理了多个用于车辆再识别的基线模型,包括AI City Challenge 2018的比赛代码、两流多任务学习网络、VeRi的报告、双流Siamese神经网络、基于三元组损失和交叉熵损失的方法,以及针对VeRI和VehicleID数据集的基线。此外,还提到了一种变分表示学习的车辆再识别方法。
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