[
    {
        "Variant name": "main",
        "Reviewer name": "David Coeurjolly <david.coeurjolly@liris.cnrs.fr>",
        "Is master variant (boolean)": true,
        "Is variant deprecated (boolean)": false,
        "Title": "What characterizes personalities of graphic designs?",
        "DOI": "10.1145/3197517.3201355",
        "Year": 2018,
        "ACM Keywords": [
            "Perception",
            "Neural networks"
        ],
        "Topic {Rendering, Animation and Simulation, Geometry, Images, Virtual Reality, Fabrication}": "Images",
        "Co-authors from academia (boolean)": true,
        "Co-authors from industry (boolean)": false,
        "ACM Open Access (boolean)": false,
        "PDF on the authors' webpage / institution (boolean)": true,
        "PDF URL": "http://nxzhao.com/projects/design_personality/Graphic_Design_Personality_SIG18_zhao.pdf",
        "PDF on Arxiv or any openarchive initiatives (boolean)": false,
        "Arxiv/OAI page URL": "",
        "Project URL": "http://nxzhao.com/projects/design_personality/",
        "Code available (boolean)": true,
        "If code not available, pseudo-code available (boolean)": false,
        "If pseudo-code, could the paper be trivially implemented? {0..4}": "",
        "Code URL": "http://nxzhao.com/projects/design_personality/personality_scoring_network_SIG18.zip",
        "Code URL2": "",
        "MD5 sum (for archives)": "5b0a261301f64d12ef9bb70a11ccd721",
        "git/hg/svn commit hash or revision number": "",
        "MD5 sum (for archives) URL2": "",
        "git/hg/svn commit hash or revision number URL2": "",
        "Software Heritage permalink": "",
        "Software type {Code, Binary, Partial Code}": "Code",
        "Code License (if any)": "This code is copyrighted by the authors and is for non-commercial research purposes only. Please contact nanxuanzhao@gmail.com if you are interested in licensing for commercial purposes",
        "Are the code authors explicit? (boolean)": false,
        "Build/Configure mechanism": "Not applicable (python, Matlab..)",
        "Dependencies": "keras/theano/h5py/tensorflow",
        "Does the software require paywall/proprietary software/material (boolean)?": false,
        "Does the code need data (not examples) (boolean)": true,
        "Nature of the data (pretrained model, LUT...)": "Training data, Pre-trained models / Hardcoded data / lookup tables /...",
        "License of the data": "",
        "Able to perform a replicability test (boolean)": false,
        "If not able to perform a test, was it due to missing hardware/software? (boolean)": false,
        "Documentation score {0=NA,1,2,3}": 0,
        "Dependencies score {0=NA, 1,2,3,4,5}": 5,
        "Build/configure score {0=NA, 1,2,3,4,5}": 0,
        "Fixing bugs score (if any) {0=NA, 1,2,3,4,5}": 0,
        "Replicate paper results score {0=NA, 1,2,3,4,5}": 0,
        "Adaptability score to other contexts {0=NA, 1,2,3,4,5}": 0,
        "Time spent for the test (code download to first successful run, [0,10], 10min slots, 100min max)": 3,
        "Operating system for the test": "Linux",
        "Build instructions/comments": "The authors provide both the training data and the pretrained models. However, I obtained tensorflow errors when trying to test the model:\n\nValueError: Negative dimension size caused by subtracting 4 from 3 for 'MaxPool' (op: 'MaxPool') with input shapes: [?,3,300,64].",
        "Misc. comments": "",
        "Software language": "Python"
    }
]