{"url":"/task/binarization","name":"Binarization","slug":"binarization","description_markdown":null,"categories":[],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":433,"papers_with_code":184,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":17,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[{"url":"/dataset/cifar-10","name":"CIFAR-10","full_name":"CIFAR-10","num_papers_in_archive":16145},{"url":"/dataset/imagenet","name":"ImageNet","full_name":"","num_papers_in_archive":15430},{"url":"/dataset/cifar-100","name":"CIFAR-100","full_name":"","num_papers_in_archive":9045},{"url":"/dataset/jhu-crowd","name":"JHU-CROWD","full_name":"","num_papers_in_archive":22},{"url":"/dataset/fdst","name":"FDST","full_name":"Fudan-ShanghaiTech","num_papers_in_archive":18},{"url":"/dataset/dibco-and-h-dibco","name":"DIBCO and H_DIBCO","full_name":"(Handwritten) Document Image Binarization Competition (DIBCO)","num_papers_in_archive":14},{"url":"/dataset/dibco-2011","name":"DIBCO 2011","full_name":"","num_papers_in_archive":7},{"url":"/dataset/h-dibco-2016","name":"H-DIBCO 2016","full_name":"","num_papers_in_archive":7},{"url":"/dataset/dibco-2017","name":"DIBCO 2017","full_name":"","num_papers_in_archive":6},{"url":"/dataset/h-dibco-2014","name":"H-DIBCO 2014","full_name":"","num_papers_in_archive":6},{"url":"/dataset/h-dibco-2018","name":"H-DIBCO 2018","full_name":"","num_papers_in_archive":6},{"url":"/dataset/dibco-2013","name":"DIBCO 2013","full_name":"","num_papers_in_archive":5},{"url":"/dataset/h-dibco-2012","name":"H-DIBCO 2012","full_name":"","num_papers_in_archive":5},{"url":"/dataset/dibco-2009","name":"DIBCO 2009","full_name":"","num_papers_in_archive":4},{"url":"/dataset/dibco-2019","name":"DIBCO 2019","full_name":"","num_papers_in_archive":4},{"url":"/dataset/h-dibco-2010","name":"H-DIBCO 2010","full_name":"","num_papers_in_archive":4},{"url":"/dataset/lrde-dbd","name":"LRDE DBD","full_name":"","num_papers_in_archive":1}],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":184,"tagged_in_all":433,"items":[{"url":"/paper/xnor-net-imagenet-classification-using-binary","title":"XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks","date":"2016-03-16","arxiv_id":"1603.05279","repositories_listed":20,"syntology":{"n":18,"n_ran":7,"n_unverified":11,"n_pointer_only":3}},{"url":"/paper/real-time-scene-text-detection-with","title":"Real-time Scene Text Detection with Differentiable Binarization","date":"2019-11-20","arxiv_id":"1911.08947","repositories_listed":15,"syntology":{"n":25,"n_ran":3,"n_unverified":22,"n_pointer_only":0}},{"url":"/paper/bimlp-compact-binary-architectures-for-vision","title":"BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons","date":"2022-12-29","arxiv_id":"2212.14158","repositories_listed":5,"syntology":null},{"url":"/paper/real-time-scene-text-detection-with-1","title":"Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion","date":"2022-02-21","arxiv_id":"2202.10304","repositories_listed":5,"syntology":null},{"url":"/paper/de-gan-a-conditional-generative-adversarial-1","title":"DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement","date":"2020-10-17","arxiv_id":"2010.08764","repositories_listed":4,"syntology":null},{"url":"/paper/read-bad-a-new-dataset-and-evaluation-scheme","title":"READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival Documents","date":"2017-05-09","arxiv_id":"1705.03311","repositories_listed":4,"syntology":null},{"url":"/paper/bit-robustly-binarized-multi-distilled","title":"BiT: Robustly Binarized Multi-distilled Transformer","date":"2022-05-25","arxiv_id":"2205.13016","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/recu-reviving-the-dead-weights-in-binary","title":"ReCU: Reviving the Dead Weights in Binary Neural Networks","date":"2021-03-23","arxiv_id":"2103.12369","repositories_listed":3,"syntology":{"n":3,"n_ran":2,"n_unverified":1,"n_pointer_only":3}},{"url":"/paper/adaptive-image-sampling-using-deep-learning","title":"Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction","date":"2018-12-27","arxiv_id":"1812.10836","repositories_listed":3,"syntology":null},{"url":"/paper/towards-the-first-adversarially-robust-neural","title":"Towards the first adversarially robust neural network model on MNIST","date":"2018-05-23","arxiv_id":"1805.09190","repositories_listed":3,"syntology":{"n":10,"n_ran":0,"n_unverified":10,"n_pointer_only":0}},{"url":"/paper/binarized-convolutional-landmark-localizers","title":"Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources","date":"2017-03-02","arxiv_id":"1703.00862","repositories_listed":3,"syntology":null},{"url":"/paper/optimal-classification-trees-for-continuous","title":"Optimal Classification Trees for Continuous Feature Data Using Dynamic Programming with Branch-and-Bound","date":"2025-01-14","arxiv_id":"2501.07903","repositories_listed":2,"syntology":null},{"url":"/paper/naf-dpm-a-nonlinear-activation-free-diffusion","title":"NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement","date":"2024-04-08","arxiv_id":"2404.05669","repositories_listed":2,"syntology":null},{"url":"/paper/pb-llm-partially-binarized-large-language","title":"PB-LLM: Partially Binarized Large Language Models","date":"2023-09-29","arxiv_id":"2310.00034","repositories_listed":2,"syntology":{"n":11,"n_ran":5,"n_unverified":6,"n_pointer_only":0}},{"url":"/paper/binarized-spectral-compressive-imaging-1","title":"Binarized Spectral Compressive Imaging","date":"2023-05-17","arxiv_id":"2305.10299","repositories_listed":2,"syntology":{"n":32,"n_ran":13,"n_unverified":19,"n_pointer_only":0}},{"url":"/paper/basic-binary-convolution-unit-for-binarized","title":"Basic Binary Convolution Unit for Binarized Image Restoration Network","date":"2022-10-02","arxiv_id":"2210.00405","repositories_listed":2,"syntology":null},{"url":"/paper/a-comprehensive-review-of-binary-neural","title":"A comprehensive review of Binary Neural Network","date":"2021-10-11","arxiv_id":"2110.06804","repositories_listed":2,"syntology":{"n":14,"n_ran":0,"n_unverified":14,"n_pointer_only":14}},{"url":"/paper/siman-sign-to-magnitude-network-binarization","title":"SiMaN: Sign-to-Magnitude Network Binarization","date":"2021-02-16","arxiv_id":"2102.07981","repositories_listed":2,"syntology":null},{"url":"/paper/fracbnn-accurate-and-fpga-efficient-binary","title":"FracBNN: Accurate and FPGA-Efficient Binary Neural Networks with Fractional Activations","date":"2020-12-22","arxiv_id":"2012.12206","repositories_listed":2,"syntology":null},{"url":"/paper/rotated-binary-neural-network","title":"Rotated Binary Neural Network","date":"2020-09-28","arxiv_id":"2009.13055","repositories_listed":2,"syntology":null},{"url":"/paper/binary-neural-networks-a-survey","title":"Binary Neural Networks: A Survey","date":"2020-03-31","arxiv_id":"2004.03333","repositories_listed":2,"syntology":null},{"url":"/paper/bidet-an-efficient-binarized-object-detector","title":"BiDet: An Efficient Binarized Object Detector","date":"2020-03-09","arxiv_id":"2003.03961","repositories_listed":2,"syntology":null},{"url":"/paper/neural-network-compression-framework-for-fast","title":"Neural Network Compression Framework for fast model inference","date":"2020-02-20","arxiv_id":"2002.08679","repositories_listed":2,"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/lutnet-learning-fpga-configurations-for","title":"LUTNet: Learning FPGA Configurations for Highly Efficient Neural Network Inference","date":"2019-10-24","arxiv_id":"1910.12625","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/ir-net-forward-and-backward-information","title":"Forward and Backward Information Retention for Accurate Binary Neural Networks","date":"2019-09-24","arxiv_id":"1909.10788","repositories_listed":2,"syntology":null},{"url":"/paper/making-classification-competitive-for-deep","title":"Classification is a Strong Baseline for Deep Metric Learning","date":"2018-11-30","arxiv_id":"1811.12649","repositories_listed":2,"syntology":{"n":5,"n_ran":0,"n_unverified":5,"n_pointer_only":0}},{"url":"/paper/a-selectional-auto-encoder-approach-for","title":"A selectional auto-encoder approach for document image binarization","date":"2017-06-30","arxiv_id":"1706.10241","repositories_listed":2,"syntology":null},{"url":"/paper/hashnet-deep-learning-to-hash-by-continuation","title":"HashNet: Deep Learning to Hash by Continuation","date":"2017-02-02","arxiv_id":"1702.00758","repositories_listed":2,"syntology":{"n":16,"n_ran":2,"n_unverified":14,"n_pointer_only":0}},{"url":"/paper/a-sample-efficient-conditional-independence","title":"A Sample Efficient Conditional Independence Test in the Presence of Discretization","date":"2025-06-10","arxiv_id":"2506.08747","repositories_listed":1,"syntology":null},{"url":"/paper/robis-robust-binary-segmentation-for-high","title":"RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images","date":"2025-05-27","arxiv_id":"2505.21152","repositories_listed":1,"syntology":null}],"syntology_records":12,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}