DCDLearn: Multi-order Deep Cross-distance Learning for Vehicle Re-Identification

25 Mar 2020 Rixing Zhu Jianwu Fang Hongke Xu Hongkai Yu Jianru Xue

Vehicle re-identification (Re-ID) has become a popular research topic owing to its practicability in intelligent transportation systems. Vehicle Re-ID suffers the numerous challenges caused by drastic variation in illumination, occlusions, background, resolutions, viewing angles, and so on... (read more)

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Methods used in the Paper


METHOD TYPE
Triplet Loss
Loss Functions
Batch Normalization
Normalization
Residual Connection
Skip Connections
PatchGAN
Discriminators
ReLU
Activation Functions
Tanh Activation
Activation Functions
Residual Block
Skip Connection Blocks
Instance Normalization
Normalization
Convolution
Convolutions
Leaky ReLU
Activation Functions
Sigmoid Activation
Activation Functions
GAN Least Squares Loss
Loss Functions
Cycle Consistency Loss
Loss Functions
CycleGAN
Generative Models