{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/object/papers/107","list_of":"/task/object","task":"Object","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":107,"pages_in_order":107,"rows_per_page":100,"rows":[10601,10696],"of":10696,"counts":{"archive_papers_tagged":10696,"with_a_code_link":3979,"where_syntology_ran_a_sample":1043,"not_listed_spam_title":0,"listed":10696,"listed_where_code_ran":1043,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":919,"every_run_a_failure_of_syntologys_instrument":124,"listed_with_a_run_with_no_instrument_failure":919,"listed_every_run_a_failure_of_syntologys_instrument":124,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/object","prev":"/task/object/papers/106","next":null,"papers":[{"url":null,"slug":"histograms-of-sparse-codes-for-object","title":"Histograms of Sparse Codes for Object Detection","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-an-object-detector-and-extracting","title":"Improving an Object Detector and Extracting Regions Using Superpixels","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-detection-tracking-and-mapping-by","title":"Joint Detection, Tracking and Mapping by Semantic Bundle Adjustment","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-class-to-image-distance-with-object","title":"Learning Class-to-Image Distance with Object Matchings","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-collections-of-part-models-for","title":"Learning Collections of Part Models for Object Recognition","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-structured-hough-voting-for-joint","title":"Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-surf-cascade-for-fast-and-accurate","title":"Learning SURF Cascade for Fast and Accurate Object Detection","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"light-field-distortion-feature-for","title":"Light Field Distortion Feature for Transparent Object Recognition","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"looking-beyond-the-image-unsupervised","title":"Looking Beyond the Image: Unsupervised Learning for Object Saliency and Detection","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"maximum-cohesive-grid-of-superpixels-for-fast","title":"Maximum Cohesive Grid of Superpixels for Fast Object Localization","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mesh-based-semantic-modelling-for-indoor-and","title":"Mesh Based Semantic Modelling for Indoor and Outdoor Scenes","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"object-centric-anomaly-detection-by-attribute","title":"Object-Centric Anomaly Detection by Attribute-Based Reasoning","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"occlusion-patterns-for-object-class-detection","title":"Occlusion Patterns for Object Class Detection","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/online-object-tracking-a-benchmark","slug":"online-object-tracking-a-benchmark","title":"Online Object Tracking: A Benchmark","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"optimized-pedestrian-detection-for-multiple","title":"Optimized Pedestrian Detection for Multiple and Occluded People","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"perceptual-organization-and-recognition-of","title":"Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"query-adaptive-similarity-for-large-scale","title":"Query Adaptive Similarity for Large Scale Object Retrieval","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"relative-volume-constraints-for-single-view","title":"Relative Volume Constraints for Single View 3D Reconstruction","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-depth-layers-from-occlusions","title":"Revisiting Depth Layers from Occlusions","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-object-co-detection","title":"Robust Object Co-detection","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scalpel-segmentation-cascades-with-localized","title":"SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scene-parsing-by-integrating-function","title":"Scene Parsing by Integrating Function, Geometry and Appearance Models","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-paced-learning-for-long-term-tracking","title":"Self-Paced Learning for Long-Term Tracking","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-domain-adaptation-with","title":"Semi-supervised Domain Adaptation with Instance Constraints","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"slam-simultaneous-localisation-and-mapping-at","title":"SLAM++: Simultaneous Localisation and Mapping at the Level of Objects","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-preserving-object-tracking","title":"Structure Preserving Object Tracking","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"subcategory-aware-object-classification","title":"Subcategory-Aware Object Classification","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"topical-video-object-discovery-from-key","title":"Topical Video Object Discovery from Key Frames by Modeling Word Co-occurrence Prior","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tracking-people-and-their-objects","title":"Tracking People and Their Objects","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-bayesian-rooms-using-composite","title":"Understanding Bayesian Rooms Using Composite 3D Object Models","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/understanding-indoor-scenes-using-3d","slug":"understanding-indoor-scenes-using-3d","title":"Understanding Indoor Scenes Using 3D Geometric Phrases","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-joint-object-discovery-and","slug":"unsupervised-joint-object-discovery-and","title":"Unsupervised Joint Object Discovery and Segmentation in Internet Images","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"vantage-feature-frames-for-fine-grained","title":"Vantage Feature Frames for Fine-Grained Categorization","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"video-object-segmentation-through-spatially","title":"Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"voxel-cloud-connectivity-segmentation","title":"Voxel Cloud Connectivity Segmentation - Supervoxels for Point Clouds","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"video-human-segmentation-using-fuzzy-object","title":"Video Human Segmentation using Fuzzy Object Models and its Application to Body Pose Estimation of Toddlers for Behavior Studies","date":"2013-05-29","arxiv_id":"1305.6918","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-automatic-thresholding-segmentation","title":"A novel automatic thresholding segmentation method with local adaptive thresholds","date":"2013-05-22","arxiv_id":"1305.5160","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-parameter-adaptation-for-multi","title":"Automatic Parameter Adaptation for Multi-object Tracking","date":"2013-05-13","arxiv_id":"1305.2687","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-based-anomalous-pattern-discovery-in","title":"Semantic-based Anomalous Pattern Discovery in Moving Object Trajectories","date":"2013-05-08","arxiv_id":"1305.1946","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaptive-descriptor-design-for-object","title":"An Adaptive Descriptor Design for Object Recognition in the Wild","date":"2013-05-01","arxiv_id":"1305.0311","repositories_listed":0,"syntology":null},{"url":null,"slug":"bingham-procrustean-alignment-for-object","title":"Bingham Procrustean Alignment for Object Detection in Clutter","date":"2013-04-27","arxiv_id":"1304.7399","repositories_listed":0,"syntology":null},{"url":null,"slug":"reading-ancient-coin-legends-object","title":"Reading Ancient Coin Legends: Object Recognition vs. OCR","date":"2013-04-26","arxiv_id":"1304.7184","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-tracking-in-videos-approaches-and","title":"Object Tracking in Videos: Approaches and Issues","date":"2013-04-18","arxiv_id":"1304.5212","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-view-depth-estimation-from-examples","title":"Single View Depth Estimation from Examples","date":"2013-04-14","arxiv_id":"1304.3915","repositories_listed":0,"syntology":null},{"url":null,"slug":"rotational-projection-statistics-for-3d-local","title":"Rotational Projection Statistics for 3D Local Surface Description and Object Recognition","date":"2013-04-11","arxiv_id":"1304.3192","repositories_listed":0,"syntology":null},{"url":null,"slug":"amplitude-based-approach-to-evidence","title":"Amplitude-Based Approach to Evidence Accumulation","date":"2013-03-27","arxiv_id":"1304.1129","repositories_listed":0,"syntology":null},{"url":null,"slug":"geodesic-based-salient-object-detection","title":"Geodesic-based Salient Object Detection","date":"2013-02-26","arxiv_id":"1302.6557","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-mrf-energy-propagation-for-video","title":"Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters","date":"2013-01-22","arxiv_id":"1301.5356","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-semi-automated-statistical-algorithm-for","title":"A Semi-automated Statistical Algorithm for Object Separation","date":"2013-01-01","arxiv_id":"1301.0127","repositories_listed":0,"syntology":null},{"url":null,"slug":"inverting-and-visualizing-features-for-object","title":"Inverting and Visualizing Features for Object Detection","date":"2012-12-11","arxiv_id":"1212.2278","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-object-detection-and-viewpoint-estimation","title":"3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generative-model-for-parts-based-object","title":"A Generative Model for Parts-based Object Segmentation","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"context-sensitive-decision-forests-for-object","title":"Context-Sensitive Decision Forests for Object Detection","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-kernel-forests-from-multiple","title":"Semantic Kernel Forests from Multiple Taxonomies","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"shifting-weights-adapting-object-detectors","title":"Shifting Weights: Adapting Object Detectors from Image to Video","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"timely-object-recognition","title":"Timely Object Recognition","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-template-learning-for-fine","title":"Unsupervised Template Learning for Fine-Grained Object Recognition","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-recognition-using-embedded-feature","title":"Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/learning-human-activities-and-object","slug":"learning-human-activities-and-object","title":"Learning Human Activities and Object Affordances from RGB-D Videos","date":"2012-10-04","arxiv_id":"1210.1207","repositories_listed":0,"syntology":null},{"url":null,"slug":"shape-tracking-with-occlusions-via-coarse-to","title":"Shape Tracking With Occlusions via Coarse-To-Fine Region-Based Sobolev Descent","date":"2012-08-21","arxiv_id":"1208.4391","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-person-object-interactions-for","title":"Learning person-object interactions for action recognition in still images","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"maximal-cliques-that-satisfy-hard-constraints","title":"Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"object-detection-with-grammar-models","title":"Object Detection with Grammar Models","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"picodes-learning-a-compact-code-for-novel","title":"PiCoDes: Learning a Compact Code for Novel-Category Recognition","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"randomized-algorithms-for-comparison-based","title":"Randomized Algorithms for Comparison-based Search","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-labeling-of-3d-point-clouds-for","title":"Semantic Labeling of 3D Point Clouds for Indoor Scenes","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"why-the-brain-separates-face-recognition-from","title":"Why The Brain Separates Face Recognition From Object Recognition","date":"2011-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"moving-object-detection-by-detecting","title":"Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation","date":"2011-09-05","arxiv_id":"1109.0882","repositories_listed":0,"syntology":null},{"url":null,"slug":"serialising-the-iso-synaf-syntactic-object","title":"Serialising the ISO SynAF Syntactic Object Model","date":"2011-08-02","arxiv_id":"1108.0631","repositories_listed":0,"syntology":null},{"url":null,"slug":"nested-graph-words-for-object-recognition","title":"Nested Graph Words for Object Recognition","date":"2011-06-14","arxiv_id":"1106.2729","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-performance-neural-networks-for-visual","title":"High-Performance Neural Networks for Visual Object Classification","date":"2011-02-01","arxiv_id":"1102.0183","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-infinite-relational-model-for-time","title":"Dynamic Infinite Relational Model for Time-varying Relational Data Analysis","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extensions-of-generalized-binary-search-to","title":"Extensions of Generalized Binary Search to Group Identification and Exponential Costs","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/learning-to-count-objects-in-images","slug":"learning-to-count-objects-in-images","title":"Learning To Count Objects in Images","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-label-multiple-kernel-learning-by","title":"Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"object-bank-a-high-level-image-representation","title":"Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-object-detection-and-ranking","title":"Simultaneous Object Detection and Ranking with Weak Supervision","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-holistic-scene-understanding-feedback","title":"Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models","date":"2010-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-object-recognition-with-deep-belief-nets","title":"3D Object Recognition with Deep Belief Nets","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bayesian-model-for-simultaneous-image","title":"A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-additive-latent-feature-model-for","title":"An Additive Latent Feature Model for Transparent Object Recognition","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-categories-the-visual-memex-model-for","title":"Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-multi-class-learning-strategies-in","title":"Evaluating multi-class learning strategies in a generative hierarchical framework for object detection","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-human-multiple-object-tracking-as","title":"Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"filtering-abstract-senses-from-image-search","title":"Filtering Abstract Senses From Image Search Results","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"individuation-identification-and-object","title":"Individuation, Identification and Object Discovery","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-models-of-object-structure","title":"Learning models of object structure","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"occlusive-components-analysis","title":"Occlusive Components Analysis","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"region-based-segmentation-and-object","title":"Region-based Segmentation and Object Detection","date":"2009-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/a-semi-automatic-system-for-ground-truth","slug":"a-semi-automatic-system-for-ground-truth","title":"A Semi-automatic System for Ground Truth Generation of Soccer Video Sequences","date":"2009-10-06","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-shape-aware-model-for-semi-supervised","title":"A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-ideal-observer-model-of-infant-object","title":"An ideal observer model of infant object perception","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-a-discriminative-hidden-part-model","title":"Learning a discriminative hidden part model for human action recognition","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mcboost-multiple-classifier-boosting-for","title":"MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"rapid-object-detection-using-a-boosted","title":"Rapid Object Detection using a Boosted Cascade of Simple Features","date":"2003-04-15","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/solving-the-multiple-instance-problem-with","slug":"solving-the-multiple-instance-problem-with","title":"Solving the multiple instance problem with axis-parallel rectangles","date":"1997-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"2eff0091311eab47462102e0f61ac9fe12e523da97fbcfd2465736a81574f3ac","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}