{"schemaVersion":1,"release":"wedraw-v3","totalClasses":413,"totalReferences":229745,"addedClasses":54,"dimensions":96,"files":{"catalog.json":{"sha256":"611c692d3327a0c1e181bfb59f6d122489e4fa38c1337342fea70bc5de0dd102","bytes":229799},"prototypes.json":{"sha256":"ec7ff067b112b472ab2d208b3099c859c5dc05d46a036e45e14724064d4ec784","bytes":255580},"encoder.json":{"sha256":"84cee81bdf93e17e2db1efcd5b562697d3c3c8c7617de57205287adf6f7e90a8","bytes":827589},"features.mjs":{"sha256":"b9763ad0f5129c5969686b3391bd9dce824823a6bdce6b71d1c44a85c6509dec","bytes":2765},"screening.json":{"sha256":"e751d2a552505e73282146a07a830285dd67496a59c98e2ef67936bea069ff60","bytes":27850}},"modelSelection":{"chosen":"seva-v1","baselineCalibrationUtility":0.31541884868751974,"alternateCalibrationUtility":0.37120396454709426,"baselineAdmitted":51,"alternateAdmitted":58},"candidateClasses":78,"candidateReferences":29617,"omittedAfterCalibration":["airbag","badger","baseball-glove","bassinet","beanie","coaster","crepe","doorknocker","enchilada","hula-hoop","kneepad","knitting-needle","mango","odometer","quesadilla","quiche","ravioli","taillight","toilet-paper","trowel"],"omittedAfterConfirmation":["bongo","cymbal","fly","margarita"],"includedNewReferences":20506,"confirmationSamples":1242,"sources":{"common":{"name":"CommonSketch","creator":"Jiho Park, Sieun Choi, Jaeyoon Seo, Minho Sohn, Yeana Kim, Jihie Kim","url":"https://huggingface.co/datasets/ziiio/CommonSketch","kind":"human_freehand","license":"CC BY 4.0","licenseUrl":"https://creativecommons.org/licenses/by/4.0/"},"quickdraw":{"name":"The Quick, Draw! Dataset","creator":"Google, Inc. and Quick, Draw! players","url":"https://github.com/googlecreativelab/quickdraw-dataset","kind":"human_freehand","license":"CC BY 4.0","licenseUrl":"https://creativecommons.org/licenses/by/4.0/"},"seva":{"name":"SEVA: Human sketch production","creator":"Kushin Mukherjee, Holly Huey, Xuanchen Lu, Yael Vinker, Rio Aguina-Kang, Ariel Shamir, Judith E. Fan; Cognitive Tools Lab","url":"https://github.com/cogtoolslab/visual_abstractions_benchmarking_public2023","license":"MIT","kind":"human_freehand","licenseUrl":"https://github.com/cogtoolslab/visual_abstractions_benchmarking_public2023/blob/main/LICENSE","datasetLicenseEvidence":"https://papers.neurips.cc/paper_files/paper/2023/file/d43621ff2dfe39d298dcd4a41937c912-Supplemental-Datasets_and_Benchmarks.pdf","licenseText":"MIT License\n\n\nCopyright (c) 2019 Cognitive Tools Lab\n\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n","sourceFile":"https://seva-benchmark.s3.us-west-2.amazonaws.com/neurips_DB_human_clean.csv","method":"Retained original human cursor traces, globally deduplicated; excluded generated drawings. No reference photographs or personal fields are redistributed.","sourceSha256":"2107e92598a3d2947441cbca1a3530cca1a8c43c5b545370d1d342988426f293","sourceBytes":1244217844},"tuberlin":{"name":"TU Berlin Sketch Dataset","creator":"Mathias Eitz, James Hays, Marc Alexa","url":"https://faculty.cc.gatech.edu/~hays/papers/Classify_sketch.pdf","licenseEvidence":"https://web.archive.org/web/20250615112619/http://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/","kind":"human_freehand","license":"CC BY 4.0","licenseUrl":"https://creativecommons.org/licenses/by/4.0/"}},"changes":"Selected distinct drawn references, normalized pen strokes or traced raster lines, extracted features, fit class medians and calibrated thresholds. SEVA sketches were grouped by source photo before fitting and testing. Separate source-specific neural weights for new classes are present only if chosen by calibration.","referenceCounting":"counts.total includes prototype-training, calibration and the first held-out positive drawings of playable categories. Independent confirmation records are additional and counted separately. Nonplayable candidates were also considered for representation training and calibration, and do not count toward the playable total. Calibration and test are never used to fit a class median. The supplemental encoder is trained from a subset of previously-used class training records plus the new candidates' training records.","evaluation":"One-object held-out drawings versus each active class. A score of at least 50 passes. closestRival is selected before evaluation by cosine of prototype anchors in the original shared embedding space. Pair exclusions additionally cover poorly separated calibrated rivals and explicit broad-subtype conflicts. Its recall ranks the target above that one rival; an equal displayed score earns half. Artist independence cannot be certified where the corpus lacks artist identifiers.","game":"Scores express calibrated visual resemblance. Human judgments on a shared two-player drawing require a separate evaluation.","modelSha256":"d83a4f25ed3466ce2421ea97038612ddb0344531169e5d9b709077804838dee7","newReferenceInventorySha256":"0927febf5d3dede02037fe43d3d0ef7fd95bbd8ef356d9a6c4b97bf0529a7134"}