Horizontal Pyramid Matching for Person Re-Identification
Authors: Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang8295-8302
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To validate the effectiveness of our proposed HPM method, extensive experiments are conducted on three popular datasets including Market-1501, Duke MTMCRe ID and CUHK03. |
| Researcher Affiliation | Collaboration | Yang Fu,1 Yunchao Wei,1 Yuqian Zhou,1 Honghui Shi,1,2 Gao Huang,3 Xinchao Wang,4 Zhiqiang Yao,5 Thomas Huang1 1IFP, Beckman Institute, UIUC, 2 IBM Research, 3Cornell University, 4Stevens Institute of Technology, 5Cloud Walk Technology |
| Pseudocode | No | The paper describes its method through text and diagrams (Figure 1, Figure 3), but it does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not include any explicit statement about open-sourcing its code or provide a link to a code repository. |
| Open Datasets | Yes | Market1501 (Zheng et al. 2015) contains 32,668 images of 1,501 labeled persons... Duke MTMC-Re ID (Ristani et al. 2016; Zheng, Zheng, and Yang 2017c) is a subset of the Duke MTMC dataset... CUHK03 (Li et al. 2014) consists of 14,097 cropped images from 1,467 identities. |
| Dataset Splits | Yes | Market-1501 ... There are 19,732 gallery images and 12,936 training images detected by DPM... including 751 identities in the training set and 750 identities in the testing set. Duke MTMC-Re ID ... There are 2,228 query images, 16,522 training images and 17,661 gallery images... CUHK03 ... adopt the new training/testing protocol proposed in (Zhong et al. 2017). |
| Hardware Specification | Yes | Our model is implemented on Pytorch platform and train with two NVIDIA TITAN X GPUs. |
| Software Dependencies | No | The paper mentions "Pytorch platform" and "Resnet50 that initialized with the weights pretrained on Image Net". However, it does not specify version numbers for PyTorch or other software libraries/dependencies. |
| Experiment Setup | Yes | we resize all the image to 384x128. ... The batch size is set to 64 and we train model for 60 epoch. The base learning rate is set to 0.1 and decay to 0.01 after 40 epochs. ... The stochastic gradient descent (SGD) with 0.9 momentum is implemented in each mini-batch... |