Cross-View Projective Dictionary Learning for Person Re-Identification
Authors: Sheng Li, Ming Shao, Yun Fu
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on the public VIPe R and CUHK Campus datasets show that our approach achieves the state-of-the-art performance. |
| Researcher Affiliation | Academia | Sheng Li Dept. of ECE Northeastern University Boston, MA, USA shengli@ece.neu.edu Ming Shao Dept. of ECE Northeastern University Boston, MA, USA mingshao@ece.neu.edu Yun Fu Dept. of ECE and College of CIS Northeastern University Boston, MA, USA yunfu@ece.neu.edu |
| Pseudocode | Yes | Algorithm 1. CPDL for Person Re-identification |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., specific repository link, explicit code release statement) for its source code. |
| Open Datasets | Yes | Experiments on the public VIPe R and CUHK Campus datasets show that our approach achieves the state-of-the-art performance. |
| Dataset Splits | Yes | We follow the evaluation protocol in [Gray and Tao, 2008]. In particular, we randomly select 316 pairs of images for training, and the remaining pairs are used for test. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers. |
| Experiment Setup | Yes | There are five parameters in our model, including α, β, λ, λ1 and λ2. In the experiments, we empirically set these parameters to achieve the best performance. In particular, α and β are set to 2 and 1, respectively. λ used in the fusion strategy is chosen in the range [0 1]. Two parameters λ1 and λ2 control the effects of cross-view interactions, and we will discuss their settings in the next section. ... We set λ1 = 1, λ2 = 2. |