SpFormer: Spatio-Temporal Modeling for Scanpaths with Transformer
Authors: Wenqi Zhong, Linzhi Yu, Chen Xia, Junwei Han, Dingwen Zhang
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct extensive experiments on four databases under three tasks. |
| Researcher Affiliation | Academia | School of Automation, Northwestern Polytechnical University, China wenqizhong@mail.nwpu.edu.cn, 15160557827@mail.nwpu.edu.cn, cxia@nwpu.edu.cn, junweihan2010@gmail.com, zhangdingwen2006yyy@gmail.com |
| Pseudocode | No | The paper describes methods using text and mathematical equations, but does not include any explicitly labeled 'Pseudocode' or 'Algorithm' blocks. |
| Open Source Code | Yes | The code can be obtained from https://github.com/wenqizhong/Sp Former. |
| Open Datasets | Yes | We apply two datasets, Saliency4ASD (Duan et al. 2019) dataset and our collected dataset, to evaluate the ASD recognition performance of the Sp Former. ... We utilize a toddler age prediction (TAP) dataset1 obtained from (Dalrymple et al. 2019)... 1https://osf.io/ugvj4 ... Koehler et al. (2014) proposed a visual perceptual task (VPT) dataset2... 2https://data.mendeley.com/datasets/8rj98pp6km/1 |
| Dataset Splits | No | The paper states 'Utrain denotes the subject set for training' and refers to previous experimental protocols for settings, but does not provide specific numerical train/validation/test dataset splits within the provided text. |
| Hardware Specification | No | The paper does not provide any specific hardware specifications such as GPU models, CPU types, or memory used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or their version numbers (e.g., Python, PyTorch, or CUDA versions) required for replication. |
| Experiment Setup | Yes | We set α = σ = 0.5, β = 1 σ = 0.5 in Eq. (20), and λ = 0.1 in Eq.( 24). |