{"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/attribute/papers/52","list_of":"/task/attribute","task":"Attribute","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":52,"pages_in_order":54,"rows_per_page":100,"rows":[5101,5200],"of":5387,"counts":{"archive_papers_tagged":5387,"with_a_code_link":1923,"where_syntology_ran_a_sample":475,"not_listed_spam_title":0,"listed":5387,"listed_where_code_ran":475,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":387,"every_run_a_failure_of_syntologys_instrument":88,"listed_with_a_run_with_no_instrument_failure":387,"listed_every_run_a_failure_of_syntologys_instrument":88,"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/attribute","prev":"/task/attribute/papers/51","next":"/task/attribute/papers/53","papers":[{"url":null,"slug":"construction-safety-risk-modeling-and","title":"Construction Safety Risk Modeling and Simulation","date":"2016-09-26","arxiv_id":"1609.07912","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimistic-and-pessimistic-neural-networks","title":"Optimistic and Pessimistic Neural Networks for Scene and Object Recognition","date":"2016-09-26","arxiv_id":"1609.07982","repositories_listed":0,"syntology":null},{"url":"/paper/from-facial-expression-recognition-to","slug":"from-facial-expression-recognition-to","title":"From Facial Expression Recognition to Interpersonal Relation Prediction","date":"2016-09-21","arxiv_id":"1609.06426","repositories_listed":0,"syntology":null},{"url":null,"slug":"price-impact-without-order-book-a-study-of","title":"Price impact without order book: A study of the OTC credit index market","date":"2016-09-15","arxiv_id":"1609.04620","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-generation-of-time-based-label-refinements","title":"On Generation of Time-based Label Refinements","date":"2016-09-12","arxiv_id":"1609.03333","repositories_listed":0,"syntology":null},{"url":null,"slug":"reliable-attribute-based-object-recognition","title":"Reliable Attribute-Based Object Recognition Using High Predictive Value Classifiers","date":"2016-09-12","arxiv_id":"1609.03619","repositories_listed":0,"syntology":null},{"url":null,"slug":"activity-networks-with-delays-an-application","title":"Activity Networks with Delays An application to toxicity analysis","date":"2016-08-26","arxiv_id":"1608.07440","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-network-for-attribute-driven","title":"Convolutional Network for Attribute-driven and Identity-preserving Human Face Generation","date":"2016-08-23","arxiv_id":"1608.06434","repositories_listed":0,"syntology":null},{"url":null,"slug":"relarm-a-rating-model-based-on-relative-pca","title":"RELARM: A rating model based on relative PCA attributes and k-means clustering","date":"2016-08-23","arxiv_id":"1608.06416","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-heuristic-scheme-for-the-cooperative-team","title":"A heuristic scheme for the Cooperative Team Orienteering Problem with Time Windows","date":"2016-08-19","arxiv_id":"1608.05485","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversified-top-k-similarity-search-in-large","title":"Diversified Top-k Similarity Search in Large Attributed Networks","date":"2016-08-18","arxiv_id":"1608.05346","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-extraction-from-product-titles-in","title":"Attribute Extraction from Product Titles in eCommerce","date":"2016-08-15","arxiv_id":"1608.04670","repositories_listed":0,"syntology":null},{"url":null,"slug":"reasoning-and-algorithm-selection-augmented","title":"Reasoning and Algorithm Selection Augmented Symbolic Segmentation","date":"2016-08-12","arxiv_id":"1608.03667","repositories_listed":0,"syntology":null},{"url":null,"slug":"solving-visual-madlibs-with-multiple-cues","title":"Solving Visual Madlibs with Multiple Cues","date":"2016-08-11","arxiv_id":"1608.03410","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepcamp-deep-convolutional-action-attribute","title":"DeepCAMP: Deep Convolutional Action & Attribute Mid-Level Patterns","date":"2016-08-10","arxiv_id":"1608.03217","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-localization-and-ranking-for","title":"End-to-End Localization and Ranking for Relative Attributes","date":"2016-08-09","arxiv_id":"1608.02676","repositories_listed":0,"syntology":null},{"url":null,"slug":"spontaneous-facial-micro-expression","title":"Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection","date":"2016-08-07","arxiv_id":"1608.02255","repositories_listed":0,"syntology":null},{"url":null,"slug":"continuation-semantics-for-multi-quantifier","title":"Continuation semantics for multi-quantifier sentences: operation-based approaches","date":"2016-07-31","arxiv_id":"1608.00255","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-organization-in-a-distributed","title":"Self-organization in a distributed coordination game through heuristic rules","date":"2016-07-31","arxiv_id":"1608.00213","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-learning-for-network-intrusion","title":"Attribute Learning for Network Intrusion Detection","date":"2016-07-28","arxiv_id":"1607.08634","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-networks-analyzed-via-1","title":"Convolutional Neural Networks Analyzed via Convolutional Sparse Coding","date":"2016-07-27","arxiv_id":"1607.08194","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-semantic-embedding-consistency-by","title":"Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification","date":"2016-07-27","arxiv_id":"1607.08085","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-based-crowd-representation-for","title":"Emotion-Based Crowd Representation for Abnormality Detection","date":"2016-07-26","arxiv_id":"1607.07646","repositories_listed":0,"syntology":null},{"url":null,"slug":"community-detection-algorithm-combining","title":"Community Detection Algorithm Combining Stochastic Block Model and Attribute Data Clustering","date":"2016-07-21","arxiv_id":"1608.00920","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-purpose-hashing","title":"Dual Purpose Hashing","date":"2016-07-19","arxiv_id":"1607.05529","repositories_listed":0,"syntology":null},{"url":null,"slug":"bag-of-attributes-for-video-event-retrieval","title":"Bag of Attributes for Video Event Retrieval","date":"2016-07-18","arxiv_id":"1607.05208","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-extended-mabac-for-multi-attribute","title":"An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers","date":"2016-07-05","arxiv_id":"1607.01254","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-recognition-from-adaptive-parts","title":"Attribute Recognition from Adaptive Parts","date":"2016-07-05","arxiv_id":"1607.01437","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-view-kernel-consensus-for-data-analysis","title":"Multi-View Kernel Consensus For Data Analysis","date":"2016-06-28","arxiv_id":"1606.08819","repositories_listed":0,"syntology":null},{"url":null,"slug":"word-sense-disambiguation-a-complex-network","title":"Word sense disambiguation: a complex network approach","date":"2016-06-25","arxiv_id":"1606.07950","repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-individual-facial-expressions-by","title":"Identifying individual facial expressions by deconstructing a neural network","date":"2016-06-23","arxiv_id":"1606.07285","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-constrained-clustering-based-approach-for","title":"A constrained clustering based approach for matching a collection of feature sets","date":"2016-06-12","arxiv_id":"1606.03731","repositories_listed":0,"syntology":null},{"url":null,"slug":"bunji-at-semeval-2016-task-5-neural-and","title":"bunji at SemEval-2016 Task 5: Neural and Syntactic Models of Entity-Attribute Relationship for Aspect-based Sentiment Analysis","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cu-nlp-at-semeval-2016-task-8-amr-parsing","title":"CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mdl-cw-a-multimodal-deep-learning-framework","title":"MDL-CW: A Multimodal Deep Learning Framework With Cross Weights","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"one-shot-learning-of-scene-locations-via","title":"One-Shot Learning of Scene Locations via Feature Trajectory Transfer","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ppp-joint-pointwise-and-pairwise-image-label","title":"PPP: Joint Pointwise and Pairwise Image Label Prediction","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"slicing-convolutional-neural-network-for","title":"Slicing Convolutional Neural Network for Crowd Video Understanding","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-learning-of-discriminative","title":"Unsupervised Learning of Discriminative Attributes and Visual Representations","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/predicting-personal-traits-from-facial-images","slug":"predicting-personal-traits-from-facial-images","title":"Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information","date":"2016-05-29","arxiv_id":"1605.09062","repositories_listed":0,"syntology":null},{"url":null,"slug":"describing-human-aesthetic-perception-by","title":"Engineering Deep Representations for Modeling Aesthetic Perception","date":"2016-05-25","arxiv_id":"1605.07699","repositories_listed":0,"syntology":null},{"url":null,"slug":"semiparametric-energy-based-probabilistic","title":"Semiparametric energy-based probabilistic models","date":"2016-05-24","arxiv_id":"1605.07371","repositories_listed":0,"syntology":null},{"url":null,"slug":"localizing-by-describing-attribute-guided","title":"Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition","date":"2016-05-20","arxiv_id":"1605.06217","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-facial-attributes-adversarially-robust","title":"Are Facial Attributes Adversarially Robust?","date":"2016-05-18","arxiv_id":"1605.05411","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-attributes-driven-multi-camera-person-re","title":"Deep Attributes Driven Multi-Camera Person Re-identification","date":"2016-05-11","arxiv_id":"1605.03259","repositories_listed":0,"syntology":null},{"url":null,"slug":"function-described-graphs-for-structural","title":"Function-Described Graphs for Structural Pattern Recognition","date":"2016-05-10","arxiv_id":"1605.02929","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-and-or-grammar-for-joint-parsing-of","title":"Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose","date":"2016-05-06","arxiv_id":"1605.02112","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-modeling-of-multidimensional-1","title":"Hierarchical Modeling of Multidimensional Data in Regularly Decomposed Spaces: Main Principles","date":"2016-05-03","arxiv_id":"1605.00961","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-attributes-equals-multi-source","title":"Learning Attributes Equals Multi-Source Domain Generalization","date":"2016-05-03","arxiv_id":"1605.00743","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-expressions-of-blame-or-praise-in","title":"Detecting Expressions of Blame or Praise in Text","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-analysis-of-linguistic","title":"Discriminative Analysis of Linguistic Features for Typological Study","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"encoding-adjective-scales-for-fine-grained","title":"Encoding Adjective Scales for Fine-grained Resources","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-tone-and-attribution-for-financial","title":"Learning Tone and Attribution for Financial Text Mining","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-advances-in-development-of-a-lexicon","title":"Recent Advances in Development of a Lexicon-Grammar of Polish: PolNet 3.0","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-layer-of-the-valence-dictionary-of","title":"Semantic Layer of the Valence Dictionary of Polish Walenty","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-networks-for-attribute","title":"Convolutional Neural Networks for Attribute-based Active Authentication on Mobile Devices","date":"2016-04-29","arxiv_id":"1604.08865","repositories_listed":0,"syntology":null},{"url":null,"slug":"crowd-counting-via-weighted-vlad-on-dense","title":"Crowd Counting via Weighted VLAD on Dense Attribute Feature Maps","date":"2016-04-29","arxiv_id":"1604.08660","repositories_listed":0,"syntology":null},{"url":"/paper/attributes-for-improved-attributes-a-multi","slug":"attributes-for-improved-attributes-a-multi","title":"Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification","date":"2016-04-25","arxiv_id":"1604.07360","repositories_listed":0,"syntology":null},{"url":null,"slug":"walk-and-learn-facial-attribute","title":"Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data","date":"2016-04-21","arxiv_id":"1604.06433","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-initial-seed-selection-algorithm-for-k","title":"An Initial Seed Selection Algorithm for K-means Clustering of Georeferenced Data to Improve Replicability of Cluster Assignments for Mapping Application","date":"2016-04-17","arxiv_id":"1604.04893","repositories_listed":0,"syntology":null},{"url":null,"slug":"reverse-engineering-and-symbolic-knowledge","title":"Reverse Engineering and Symbolic Knowledge Extraction on Łukasiewicz Fuzzy Logics using Linear Neural Networks","date":"2016-04-11","arxiv_id":"1604.02774","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-local-material-recognition-with","title":"Integrating Local Material Recognition with Large-Scale Perceptual Attribute Discovery","date":"2016-04-05","arxiv_id":"1604.01345","repositories_listed":0,"syntology":null},{"url":null,"slug":"extending-dlr-with-labelled-tuples","title":"Extending DLR with Labelled Tuples, Projections, Functional Dependencies and Objectification (full version)","date":"2016-04-04","arxiv_id":"1604.00799","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-transfer-zero-shot-object-recognition","title":"How to Transfer? Zero-Shot Object Recognition via Hierarchical Transfer of Semantic Attributes","date":"2016-04-01","arxiv_id":"1604.00326","repositories_listed":0,"syntology":null},{"url":null,"slug":"locally-epistatic-models-for-genome-wide","title":"Locally Epistatic Models for Genome-wide Prediction and Association by Importance Sampling","date":"2016-03-29","arxiv_id":"1603.08813","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-cue-zero-shot-learning-with-strong","title":"Multi-Cue Zero-Shot Learning with Strong Supervision","date":"2016-03-29","arxiv_id":"1603.08754","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-real-time-cluster-configurations-of","title":"Using real-time cluster configurations of streaming asynchronous features as online state descriptors in financial markets","date":"2016-03-22","arxiv_id":"1603.06805","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-image-simplification-and","title":"Hierarchical image simplification and segmentation based on Mumford-Shah-salient level line selection","date":"2016-03-15","arxiv_id":"1603.04838","repositories_listed":0,"syntology":null},{"url":null,"slug":"u-catch-using-color-attribute-of-image","title":"U-CATCH: Using Color ATtribute of image patCHes in binary descriptors","date":"2016-03-14","arxiv_id":"1603.04408","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-innovative-imputation-and-classification","title":"An Innovative Imputation and Classification Approach for Accurate Disease Prediction","date":"2016-03-10","arxiv_id":"1603.03281","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-red-one-on-learning-to-refer-to-things-1","title":"The red one!: On learning to refer to things based on their discriminative properties","date":"2016-03-08","arxiv_id":"1603.02618","repositories_listed":0,"syntology":null},{"url":null,"slug":"determining-the-best-attributes-for","title":"Determining the best attributes for surveillance video keywords generation","date":"2016-02-21","arxiv_id":"1602.06539","repositories_listed":0,"syntology":null},{"url":null,"slug":"face-attribute-prediction-using-off-the-shelf","title":"Face Attribute Prediction Using Off-the-Shelf CNN Features","date":"2016-02-12","arxiv_id":"1602.03935","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-imputation-of-missing-values-for","title":"Adaptive imputation of missing values for incomplete pattern classification","date":"2016-02-08","arxiv_id":"1602.02617","repositories_listed":0,"syntology":null},{"url":null,"slug":"erblox-combining-matching-dependencies-with","title":"ERBlox: Combining Matching Dependencies with Machine Learning for Entity Resolution","date":"2016-02-07","arxiv_id":"1602.02334","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-and-quantitative-evaluation-of","title":"Automatic and Quantitative evaluation of attribute discovery methods","date":"2016-02-05","arxiv_id":"1602.01940","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-mid-level-deep-representations-for","title":"Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild","date":"2016-02-04","arxiv_id":"1602.01827","repositories_listed":0,"syntology":null},{"url":null,"slug":"numerical-atrribute-extraction-from-clinical","title":"Numerical Atrribute Extraction from Clinical Texts","date":"2016-01-31","arxiv_id":"1602.00269","repositories_listed":0,"syntology":null},{"url":null,"slug":"implicit-distortion-and-fertility-models-for","title":"Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model","date":"2016-01-13","arxiv_id":"1601.03317","repositories_listed":0,"syntology":null},{"url":"/paper/multi-task-cnn-model-for-attribute-prediction","slug":"multi-task-cnn-model-for-attribute-prediction","title":"Multi-task CNN Model for Attribute Prediction","date":"2016-01-04","arxiv_id":"1601.00400","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-language-independent-model-for-introducing","title":"A Language-independent Model for Introducing a New Semantic Relation Between Adjectives and Nouns in a WordNet","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-era-of-fole-foundation","title":"The ERA of FOLE: Foundation","date":"2015-12-23","arxiv_id":"1512.07430","repositories_listed":0,"syntology":null},{"url":null,"slug":"heuristic-algorithms-for-finding-distribution","title":"Heuristic algorithms for finding distribution reducts in probabilistic rough set model","date":"2015-12-22","arxiv_id":"1512.07162","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-colors-of-single-attribute","title":"Modeling Colors of Single Attribute Variations with Application to Food Appearance","date":"2015-12-18","arxiv_id":"1512.06075","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-based-world-modeling-in-semi-static","title":"Object-based World Modeling in Semi-Static Environments with Dependent Dirichlet-Process Mixtures","date":"2015-12-02","arxiv_id":"1512.00573","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-multiplicative-framework-for","title":"A Unified Multiplicative Framework for Attribute Learning","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"attributed-grammars-for-joint-estimation-of","title":"Attributed Grammars for Joint Estimation of Human Attributes, Part and Pose","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-the-spatial-extent-of-relative","title":"Discovering the Spatial Extent of Relative Attributes","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"just-noticeable-differences-in-visual","title":"Just Noticeable Differences in Visual Attributes","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-deep-representation-with-large-scale","title":"Learning Deep Representation With Large-Scale Attributes","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-learning-with-low-rank-attribute","title":"Multi-Task Learning With Low Rank Attribute Embedding for Person Re-Identification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"realtime-edge-based-visual-odometry-for-a","title":"Realtime Edge-Based Visual Odometry for a Monocular Camera","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-zero-shot-classification-with","title":"Semi-Supervised Zero-Shot Classification With Label Representation Learning","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automatic-image-editing-learning-to","title":"Towards Automatic Image Editing: Learning to See another You","date":"2015-11-26","arxiv_id":"1511.08446","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstract-attribute-exploration-with-partial","title":"Abstract Attribute Exploration with Partial Object Descriptions","date":"2015-11-19","arxiv_id":"1511.06191","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-predicting-the-likeability-of-fashion","title":"Towards Predicting the Likeability of Fashion Images","date":"2015-11-17","arxiv_id":"1511.05296","repositories_listed":0,"syntology":null},{"url":null,"slug":"visualizing-and-understanding-deep-texture","title":"Visualizing and Understanding Deep Texture Representations","date":"2015-11-16","arxiv_id":"1511.05197","repositories_listed":0,"syntology":null},{"url":null,"slug":"transductive-zero-shot-action-recognition-by","title":"Transductive Zero-Shot Action Recognition by Word-Vector Embedding","date":"2015-11-13","arxiv_id":"1511.04458","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-heterogeneous-information-via","title":"Integrating Heterogeneous Information via Flexible Regularization Framework for Recommendation","date":"2015-11-12","arxiv_id":"1511.03759","repositories_listed":0,"syntology":null},{"url":null,"slug":"videostory-embeddings-recognize-events-when","title":"VideoStory Embeddings Recognize Events when Examples are Scarce","date":"2015-11-08","arxiv_id":"1511.02492","repositories_listed":0,"syntology":null}],"record_sha256":"f9404ce55561cd033f4a1e42b6c3db8bdc83b8af41572d350734d96f986b506f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}