{"url":"/dataset/trans10k","name":"Trans10K","full_name":null,"description_markdown":"A large-scale dataset for transparent object segmentation, named Trans10K, consisting of 10,428 images of real scenarios with carefully manual annotations, which are 10 times larger than the existing datasets. \r\n\r\nSource: [Segmenting Transparent Objects in the Wild](/paper/segmenting-transparent-objects-in-the-wild)","description_withheld":null,"homepage":"https://github.com/xieenze/Segment_Transparent_Objects","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/segmenting-transparent-objects-in-the-wild","title":"Segmenting Transparent Objects in the Wild","first_author":"Enze Xie","url":null},"license":null,"modalities":[],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["Trans10K"],"data_loaders":[{"repo":"https://github.com/xieenze/Segment_Transparent_Objects","url":"https://github.com/xieenze/Segment_Transparent_Objects","frameworks":["pytorch"]}],"num_papers_in_archive":33,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-trans10k","task":"Semantic Segmentation","dataset_variant":"Trans10K","rows":15,"metrics":["mIoU","GFLOPs"],"first_row_in_archive_order":{"model":"Trans4Trans (M)","paper":"/paper/trans4trans-efficient-transformer-for","metrics":{"GFLOPs":"34.38","mIoU":"75.14%"},"code_links":[{"title":"jamycheung/Trans4Trans","url":"https://github.com/jamycheung/Trans4Trans"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/trans4trans-efficient-transformer-for","title":"Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World","date":"2021-07-07","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/segmenting-transparent-object-in-the-wild","title":"Segmenting Transparent Object in the Wild with Transformer","date":"2021-01-21","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/segmenting-transparent-objects-in-the-wild","title":"Segmenting Transparent Objects in the Wild","date":"2020-03-31","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":3,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dual-attention-network-for-scene-segmentation","title":"Dual Attention Network for Scene Segmentation","date":"2018-09-09","rows_on_this_dataset":1,"code_links":12,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":0,"samples_unverified":7,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ocnet-object-context-network-for-scene","title":"OCNet: Object Context Network for Scene Parsing","date":"2018-09-04","rows_on_this_dataset":1,"code_links":8,"syntology":null},{"paper":"/paper/bisenet-bilateral-segmentation-network-for","title":"BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation","date":"2018-08-02","rows_on_this_dataset":1,"code_links":21,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":18,"samples_ran":6,"samples_unverified":12,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/denseaspp-for-semantic-segmentation-in-street","title":"DenseASPP for Semantic Segmentation in Street Scenes","date":"2018-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/encoder-decoder-with-atrous-separable","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","date":"2018-02-07","rows_on_this_dataset":1,"code_links":78,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":72,"samples_ran":43,"samples_unverified":29,"pointer_only_for_licence":40,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/icnet-for-real-time-semantic-segmentation-on","title":"ICNet for Real-Time Semantic Segmentation on High-Resolution Images","date":"2017-04-27","rows_on_this_dataset":1,"code_links":18,"syntology":null},{"paper":"/paper/pyramid-scene-parsing-network","title":"Pyramid Scene Parsing Network","date":"2016-12-04","rows_on_this_dataset":1,"code_links":67,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":29,"samples_ran":7,"samples_unverified":22,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/refinenet-multi-path-refinement-networks-for","title":"RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation","date":"2016-11-20","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":1,"samples_unverified":6,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/u-net-convolutional-networks-for-biomedical","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","date":"2015-05-18","rows_on_this_dataset":1,"code_links":487,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":757,"samples_ran":510,"samples_unverified":247,"pointer_only_for_licence":426,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/fully-convolutional-networks-for-semantic-1","title":"Fully Convolutional Networks for Semantic Segmentation","date":"2014-11-14","rows_on_this_dataset":1,"code_links":51,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":3,"samples_unverified":1,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":8,"samples_harvested":903,"samples_ran":573,"samples_unverified":330,"pointer_only_for_licence":482,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}