Deep View-Aware Metric Learning for Person Re-Identification
Authors: Pu Chen, Xinyi Xu, Cheng Deng
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiment results on datasets CUHK01, CUHK03, and PRID2011 demonstrate the superiority of our method compared with state-of-the-art approaches. |
| Researcher Affiliation | Academia | School of Electronic Engineering, Xidian University, Xi an 710071, China puchen@stu.xidian.edu.cn, xyxu.xd@gmail.com, chdeng@mail.xidian.edu.cn |
| Pseudocode | Yes | Algorithm 1 Back Propagation gradient |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., specific repository link, explicit code release statement) for the source code of the described methodology. |
| Open Datasets | Yes | We evaluate our method on three datasets, CUHK03 [Li et al., 2014], CUHK01 [Li et al., 2012] and PRID2011 [Hirzer et al., 2011]. |
| Dataset Splits | Yes | CUHK03 dataset contains 13164 images from 1360 persons. We select 1160 persons for training, 100 for validation and 100 for testing following the same setting as [Li et al., 2014] and [Ahmed et al., 2015]. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types) used for running its experiments. |
| Software Dependencies | No | The paper mentions general components like 'ReLU layer' and 'Batch Normalization (BN) layer' and references to CNN architectures, but does not provide specific software names with version numbers. |
| Experiment Setup | Yes | All the images are resized to 128 64 before being fed to the network and the batchsize of the input is 64. For identity classifier, we first pretrain a model on CUHK03 and the learning rate is set to 0.001, then finetune this model with learning rate 0.002. We picked a set of optimal loss weights α1 = 0.4, α2 = 0.4, α3 = 0.2 experimentally. And all the margin parameters β1, β2, β3 are set to 1 [Song et al., 2016]. |