{"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":"/method/triplet-loss/papers/3","list_of":"/method/triplet-loss","method":"Triplet Loss","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":3,"pages_in_order":5,"rows_per_page":100,"rows":[201,300],"of":424,"counts":{"archive_papers_tagged":424,"with_a_code_link":161,"where_syntology_ran_a_sample":22,"not_listed_spam_title":0,"listed":424,"listed_where_code_ran":22,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":20,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":20,"listed_every_run_a_failure_of_syntologys_instrument":2,"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":"/method/triplet-loss","prev":"/method/triplet-loss/papers/2","next":"/method/triplet-loss/papers/4","papers":[{"paper":null,"slug":"lookup-or-exploratory-what-is-your-search","title":"Lookup or Exploratory: What is Your Search Intent?","date":"2021-10-09","arxiv_id":"2110.04640","n_code_links":0,"syntology":null},{"paper":null,"slug":"rankingmatch-delving-into-semi-supervised-1","title":"RankingMatch: Delving into Semi-Supervised Learning with Consistency Regularization and Ranking Loss","date":"2021-10-09","arxiv_id":"2110.04430","n_code_links":0,"syntology":null},{"paper":null,"slug":"scale-invariant-domain-generalization-image","title":"Scale Invariant Domain Generalization Image Recapture Detection","date":"2021-10-07","arxiv_id":"2110.03496","n_code_links":0,"syntology":null},{"paper":null,"slug":"mask-or-non-mask-robust-face-mask-detector","title":"Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learning","date":"2021-10-01","arxiv_id":"2110.00523","n_code_links":0,"syntology":null},{"paper":null,"slug":"assessing-two-novel-distance-based-loss","title":"Assessing two novel distance-based loss functions for few-shot image classification","date":"2021-09-29","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"scenario-aware-speech-recognition","title":"Scenario Aware Speech Recognition: Advancements for Apollo Fearless Steps & CHiME-4 Corpora","date":"2021-09-23","arxiv_id":"2109.11086","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-the-outcome-of-team-movements","title":"Predicting the outcome of team movements -- Player time series analysis using fuzzy and deep methods for representation learning","date":"2021-09-13","arxiv_id":"2109.07570","n_code_links":0,"syntology":null},{"paper":"/paper/pairwise-supervised-contrastive-learning-of","slug":"pairwise-supervised-contrastive-learning-of","title":"Pairwise Supervised Contrastive Learning of Sentence Representations","date":"2021-09-12","arxiv_id":"2109.05424","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["amazon-research/sentence-representations"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"multi-task-triplet-loss-for-named-entity","title":"Multi-Task Triplet Loss for Named Entity Recognition using Supplementary Text","date":"2021-08-31","arxiv_id":"2109.13736","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-and-mitigating-annotation-bias","title":"Understanding and Mitigating Annotation Bias in Facial Expression Recognition","date":"2021-08-19","arxiv_id":"2108.08504","n_code_links":0,"syntology":null},{"paper":null,"slug":"video-person-re-identification-using","title":"Video Person Re-identification using Attribute-enhanced Features","date":"2021-08-16","arxiv_id":"2108.06946","n_code_links":0,"syntology":null},{"paper":"/paper/agkd-bml-defense-against-adversarial-attack","slug":"agkd-bml-defense-against-adversarial-attack","title":"AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning","date":"2021-08-13","arxiv_id":"2108.06017","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["hongw579/agkd-bml"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/memory-based-semantic-segmentation-for-off","slug":"memory-based-semantic-segmentation-for-off","title":"Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments","date":"2021-08-12","arxiv_id":"2108.05635","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-joint-embedding-with-modality","title":"Learning Joint Embedding with Modality Alignments for Cross-Modal Retrieval of Recipes and Food Images","date":"2021-08-09","arxiv_id":"2108.03788","n_code_links":0,"syntology":null},{"paper":null,"slug":"triplet-contrastive-learning-for-brain-tumor","title":"Triplet Contrastive Learning for Brain Tumor Classification","date":"2021-08-08","arxiv_id":"2108.03611","n_code_links":0,"syntology":null},{"paper":null,"slug":"ducn-dual-children-network-for-medical","title":"DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19","date":"2021-08-03","arxiv_id":"2108.01997","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-deep-feature-calibration-for-cross","title":"Efficient Deep Feature Calibration for Cross-Modal Joint Embedding Learning","date":"2021-08-02","arxiv_id":"2108.00705","n_code_links":0,"syntology":null},{"paper":null,"slug":"my-eyes-are-up-here-promoting-focus-on","title":"My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition","date":"2021-08-02","arxiv_id":"2108.00996","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-ranking-with-adaptive-margin-triplet","title":"Deep Ranking with Adaptive Margin Triplet Loss","date":"2021-07-13","arxiv_id":"2107.06187","n_code_links":0,"syntology":null},{"paper":"/paper/magnification-independent-histopathological","slug":"magnification-independent-histopathological","title":"Magnification-independent Histopathological Image Classification with Similarity-based Multi-scale Embeddings","date":"2021-07-02","arxiv_id":"2107.01063","n_code_links":1,"syntology":null},{"paper":"/paper/domain-adaptation-for-person-re","slug":"domain-adaptation-for-person-re","title":"Domain adaptation for person re-identification on new unlabeled data using AlignedReID++","date":"2021-06-29","arxiv_id":"2106.15693","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-graphs-for-knowledge-transfer-with","title":"Learning Graphs for Knowledge Transfer With Limited Labels","date":"2021-06-19","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/disentangling-semantic-to-visual-confusion","slug":"disentangling-semantic-to-visual-confusion","title":"Disentangling Semantic-to-visual Confusion for Zero-shot Learning","date":"2021-06-16","arxiv_id":"2106.08605","n_code_links":1,"syntology":null},{"paper":"/paper/compositional-sketch-search","slug":"compositional-sketch-search","title":"Compositional Sketch Search","date":"2021-06-15","arxiv_id":"2106.08009","n_code_links":1,"syntology":null},{"paper":"/paper/atlas-based-representation-and-metric","slug":"atlas-based-representation-and-metric","title":"Atlas Based Representation and Metric Learning on Manifolds","date":"2021-06-13","arxiv_id":"2106.07062","n_code_links":1,"syntology":null},{"paper":null,"slug":"robust-representation-learning-via-perceptual","title":"Robust Representation Learning via Perceptual Similarity Metrics","date":"2021-06-11","arxiv_id":"2106.06620","n_code_links":0,"syntology":null},{"paper":"/paper/sdgmnet-statistic-based-dynamic-gradient","slug":"sdgmnet-statistic-based-dynamic-gradient","title":"SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning","date":"2021-06-08","arxiv_id":"2106.04434","n_code_links":1,"syntology":null},{"paper":"/paper/vs-net-voting-with-segmentation-for-visual","slug":"vs-net-voting-with-segmentation-for-visual","title":"VS-Net: Voting with Segmentation for Visual Localization","date":"2021-05-23","arxiv_id":"2105.10886","n_code_links":1,"syntology":{"ran":8,"of":15,"n_ran_checked":7,"n_instrument":1,"unverified":7,"pointer_only":0,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 1 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 7 unverified","official":{"repos":["zju3dv/VS-Net"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":5,"n_ran_no_instrument_failure":7,"n_unverified":7,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"discriminative-generative-dual-memory-video","title":"Discriminative-Generative Dual Memory Video Anomaly Detection","date":"2021-04-29","arxiv_id":"2104.14430","n_code_links":0,"syntology":null},{"paper":"/paper/on-the-unreasonable-effectiveness-of-1","slug":"on-the-unreasonable-effectiveness-of-1","title":"On the Unreasonable Effectiveness of Centroids in Image Retrieval","date":"2021-04-28","arxiv_id":"2104.13643","n_code_links":3,"syntology":null},{"paper":null,"slug":"sketch-qnet-a-quadruplet-convnet-for-color","title":"Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval","date":"2021-04-22","arxiv_id":"2104.11130","n_code_links":0,"syntology":null},{"paper":null,"slug":"crossatnet-a-novel-cross-attention-based","title":"CrossATNet - A Novel Cross-Attention Based Framework for Sketch-Based Image Retrieval","date":"2021-04-20","arxiv_id":"2104.09918","n_code_links":0,"syntology":null},{"paper":"/paper/solving-inefficiency-of-self-supervised","slug":"solving-inefficiency-of-self-supervised","title":"Solving Inefficiency of Self-supervised Representation Learning","date":"2021-04-18","arxiv_id":"2104.08760","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"0 ran · 2 unverified","official":{"repos":["wanggrun/triplet"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":null,"slug":"color-variants-identification-via-contrastive","title":"Color Variants Identification in Fashion e-commerce via Contrastive Self-Supervised Representation Learning","date":"2021-04-17","arxiv_id":"2104.08581","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrating-information-theory-and","title":"Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval","date":"2021-04-11","arxiv_id":"2104.04991","n_code_links":0,"syntology":null},{"paper":"/paper/reducing-representation-drift-in-online","slug":"reducing-representation-drift-in-online","title":"New Insights on Reducing Abrupt Representation Change in Online Continual Learning","date":"2021-04-11","arxiv_id":"2104.05025","n_code_links":2,"syntology":{"ran":3,"of":4,"n_ran_checked":2,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["naderAsadi/AML","pclucas14/aml"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/combined-depth-space-based-architecture","slug":"combined-depth-space-based-architecture","title":"Combined Depth Space based Architecture Search For Person Re-identification","date":"2021-04-09","arxiv_id":"2104.04163","n_code_links":1,"syntology":null},{"paper":null,"slug":"siam-reid-confuser-aware-siamese-tracker-with","title":"SiamReID: Confuser Aware Siamese Tracker with Re-identification Feature","date":"2021-04-08","arxiv_id":"2104.03510","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-self-adaptive-metric-learning-on-the","title":"Towards Self-Adaptive Metric Learning On the Fly","date":"2021-04-03","arxiv_id":"2104.01495","n_code_links":0,"syntology":null},{"paper":"/paper/contrastively-learning-visual-attention-as","slug":"contrastively-learning-visual-attention-as","title":"Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping","date":"2021-04-02","arxiv_id":"2104.00878","n_code_links":1,"syntology":null},{"paper":null,"slug":"identity-aware-cyclegan-for-face-photo-sketch","title":"Identity-Aware CycleGAN for Face Photo-Sketch Synthesis and Recognition","date":"2021-03-30","arxiv_id":"2103.16019","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-similarity-learning-for-sports-team","title":"Deep Similarity Learning for Sports Team Ranking","date":"2021-03-25","arxiv_id":"2103.13736","n_code_links":0,"syntology":null},{"paper":"/paper/coarse-to-fine-domain-adaptive-semantic","slug":"coarse-to-fine-domain-adaptive-semantic","title":"Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization","date":"2021-03-24","arxiv_id":"2103.13041","n_code_links":0,"syntology":null},{"paper":null,"slug":"semi-supervised-learning-for-bone-mineral","title":"Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images","date":"2021-03-24","arxiv_id":"2103.13482","n_code_links":0,"syntology":null},{"paper":"/paper/improving-image-co-segmentation-via-deep","slug":"improving-image-co-segmentation-via-deep","title":"Improving Image co-segmentation via Deep Metric Learning","date":"2021-03-19","arxiv_id":"2103.10670","n_code_links":0,"syntology":null},{"paper":null,"slug":"unified-batch-all-triplet-loss-for-visible","title":"Unified Batch All Triplet Loss for Visible-Infrared Person Re-identification","date":"2021-03-08","arxiv_id":"2103.04607","n_code_links":0,"syntology":null},{"paper":null,"slug":"harnessing-geometric-constraints-from","title":"Harnessing Geometric Constraints from Emotion Labels to improve Face Verification","date":"2021-03-05","arxiv_id":"2103.03862","n_code_links":0,"syntology":null},{"paper":null,"slug":"npt-loss-a-metric-loss-with-implicit-mining","title":"NPT-Loss: A Metric Loss with Implicit Mining for Face Recognition","date":"2021-03-05","arxiv_id":"2103.03503","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-vehicle-re-identification-via","slug":"unsupervised-vehicle-re-identification-via","title":"Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary","date":"2021-03-03","arxiv_id":"2103.02250","n_code_links":1,"syntology":null},{"paper":"/paper/a-body-part-embedding-model-with-datasets-for","slug":"a-body-part-embedding-model-with-datasets-for","title":"A Body Part Embedding Model With Datasets for Measuring 2D Human Motion Similarity","date":"2021-03-02","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"triplet-loss-based-embeddings-for-forensic","title":"Triplet loss based embeddings for forensic speaker identification in Spanish","date":"2021-02-24","arxiv_id":"2102.12564","n_code_links":0,"syntology":null},{"paper":null,"slug":"query-by-example-keyword-spotting-system","title":"Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Loss","date":"2021-02-14","arxiv_id":"2102.07061","n_code_links":0,"syntology":null},{"paper":null,"slug":"driver2vec-driver-identification-from","title":"Driver2vec: Driver Identification from Automotive Data","date":"2021-02-10","arxiv_id":"2102.05234","n_code_links":0,"syntology":null},{"paper":"/paper/multi-level-distance-regularization-for-deep","slug":"multi-level-distance-regularization-for-deep","title":"Multi-level Distance Regularization for Deep Metric Learning","date":"2021-02-08","arxiv_id":"2102.04223","n_code_links":1,"syntology":null},{"paper":null,"slug":"mots-r-cnn-cosine-margin-triplet-loss-for","title":"MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking","date":"2021-02-06","arxiv_id":"2102.03512","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-aware-weakly-supervised-metric","title":"Multimodal-Aware Weakly Supervised Metric Learning with Self-weighting Triplet Loss","date":"2021-02-03","arxiv_id":"2102.02670","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-nir-to-vis-face-recognition-via-part","title":"A NIR-to-VIS face recognition via part adaptive and relation attention module","date":"2021-02-01","arxiv_id":"2102.00689","n_code_links":0,"syntology":null},{"paper":null,"slug":"event-driven-news-stream-clustering-using","title":"Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings","date":"2021-01-26","arxiv_id":"2101.11059","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-stage-cnn-based-wood-log-recognition","title":"Two-stage CNN-based wood log recognition","date":"2021-01-12","arxiv_id":"2101.04450","n_code_links":0,"syntology":null},{"paper":null,"slug":"entropy-based-uncertainty-calibration-for","title":"Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning","date":"2021-01-09","arxiv_id":"2101.03292","n_code_links":0,"syntology":null},{"paper":null,"slug":"havana-hierarchical-and-variation-normalized","title":"HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person Re-identification","date":"2021-01-06","arxiv_id":"2101.02568","n_code_links":0,"syntology":null},{"paper":null,"slug":"dam-discrepancy-alignment-metric-for-face","title":"DAM: Discrepancy Alignment Metric for Face Recognition","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-visual-representations-for","title":"Enhancing Visual Representations for Efficient Object Recognition during Online Distillation","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/video-geo-localization-employing-geo-temporal","slug":"video-geo-localization-employing-geo-temporal","title":"Video Geo-Localization Employing Geo-Temporal Feature Learning and GPS Trajectory Smoothing","date":"2021-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"person-re-identification-with-adversarial","title":"Person Re-identification with Adversarial Triplet Embedding","date":"2020-12-28","arxiv_id":"2012.14057","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-assessment-of-gans-for-identity-related","title":"An Assessment of GANs for Identity-related Applications","date":"2020-12-18","arxiv_id":"2012.10553","n_code_links":0,"syntology":null},{"paper":null,"slug":"r-2-net-relation-of-relation-learning-network","title":"R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching","date":"2020-12-16","arxiv_id":"2012.08920","n_code_links":0,"syntology":null},{"paper":null,"slug":"one-shot-learning-with-triplet-loss-for","title":"One-Shot Learning with Triplet Loss for Vegetation Classification Tasks","date":"2020-12-14","arxiv_id":"2012.07403","n_code_links":0,"syntology":null},{"paper":"/paper/strong-but-simple-baseline-with-dual","slug":"strong-but-simple-baseline-with-dual","title":"Strong but Simple Baseline with Dual-Granularity Triplet Loss for Visible-Thermal Person Re-Identification","date":"2020-12-09","arxiv_id":"2012.05010","n_code_links":1,"syntology":null},{"paper":"/paper/vlpd-net-a-registration-aided-domain","slug":"vlpd-net-a-registration-aided-domain","title":"A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition","date":"2020-12-09","arxiv_id":"2012.05018","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-hyperbolic-representations-for-1","title":"Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations","date":"2020-12-03","arxiv_id":"2012.01644","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-deep-metric-learning-method-for-biomedical","title":"A Deep Metric Learning Method for Biomedical Passage Retrieval","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-two-phase-prototypical-network-model-for","title":"A Two-phase Prototypical Network Model for Incremental Few-shot Relation Classification","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/fast-adversarial-robustness-certification-of","slug":"fast-adversarial-robustness-certification-of","title":"Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/the-dilemma-of-trihard-loss-and-an-element","slug":"the-dilemma-of-trihard-loss-and-an-element","title":"The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-Identification","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"tie-your-embeddings-down-cross-modal-latent","title":"Tie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding","date":"2020-11-18","arxiv_id":"2011.09044","n_code_links":0,"syntology":null},{"paper":null,"slug":"vector-embeddings-with-subvector-permutation","title":"Vector Embeddings with Subvector Permutation Invariance using a Triplet Enhanced Autoencoder","date":"2020-11-18","arxiv_id":"2011.09550","n_code_links":0,"syntology":null},{"paper":null,"slug":"application-of-computer-vision-techniques-for","title":"Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code","date":"2020-11-16","arxiv_id":"2011.07747","n_code_links":0,"syntology":null},{"paper":null,"slug":"illumination-normalization-by-partially","title":"Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function","date":"2020-11-06","arxiv_id":"2011.03428","n_code_links":0,"syntology":null},{"paper":null,"slug":"set-augmented-triplet-loss-for-video-person","title":"Set Augmented Triplet Loss for Video Person Re-Identification","date":"2020-11-02","arxiv_id":"2011.00774","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-self-supervised-scene-flow","slug":"adversarial-self-supervised-scene-flow","title":"Adversarial Self-Supervised Scene Flow Estimation","date":"2020-11-01","arxiv_id":"2011.00551","n_code_links":1,"syntology":null},{"paper":"/paper/improving-word-recognition-using-multiple","slug":"improving-word-recognition-using-multiple","title":"Improving Word Recognition using Multiple Hypotheses and Deep Embeddings","date":"2020-10-27","arxiv_id":"2010.14411","n_code_links":1,"syntology":null},{"paper":"/paper/lcd-line-clustering-and-description-for-place","slug":"lcd-line-clustering-and-description-for-place","title":"LCD -- Line Clustering and Description for Place Recognition","date":"2020-10-21","arxiv_id":"2010.10867","n_code_links":1,"syntology":null},{"paper":"/paper/audio-based-near-duplicate-video-retrieval","slug":"audio-based-near-duplicate-video-retrieval","title":"Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning","date":"2020-10-17","arxiv_id":"2010.08737","n_code_links":1,"syntology":null},{"paper":null,"slug":"film-a-fast-interpretable-and-low-rank-metric","title":"FILM: A Fast, Interpretable, and Low-rank Metric Learning Approach for Sentence Matching","date":"2020-10-12","arxiv_id":"2010.05523","n_code_links":0,"syntology":null},{"paper":"/paper/understanding-self-supervised-learning-with","slug":"understanding-self-supervised-learning-with","title":"Understanding Self-supervised Learning with Dual Deep Networks","date":"2020-10-01","arxiv_id":"2010.00578","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/luckmatters"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/acceleration-of-large-margin-metric-learning","slug":"acceleration-of-large-margin-metric-learning","title":"Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling","date":"2020-09-29","arxiv_id":"2009.14244","n_code_links":1,"syntology":null},{"paper":null,"slug":"one-shot-learning-based-classification-for","title":"One-Shot learning based classification for segregation of plastic waste","date":"2020-09-29","arxiv_id":"2009.13953","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-triplet-loss-person-re-identification","title":"Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss","date":"2020-09-22","arxiv_id":"2009.10295","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-domain-adaptation-for-person-re","title":"Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling","date":"2020-09-20","arxiv_id":"2009.09445","n_code_links":0,"syntology":null},{"paper":"/paper/domain-invariant-similarity-activation-map","slug":"domain-invariant-similarity-activation-map","title":"Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization","date":"2020-09-16","arxiv_id":"2009.07719","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-detection-for-face-manipulation","title":"Deep Detection for Face Manipulation","date":"2020-09-13","arxiv_id":"2009.05934","n_code_links":0,"syntology":null},{"paper":"/paper/deep-metric-learning-meets-deep-clustering-an","slug":"deep-metric-learning-meets-deep-clustering-an","title":"Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding","date":"2020-09-09","arxiv_id":"2009.04091","n_code_links":1,"syntology":null},{"paper":null,"slug":"diversified-mutual-learning-for-deep-metric","title":"Diversified Mutual Learning for Deep Metric Learning","date":"2020-09-09","arxiv_id":"2009.04170","n_code_links":0,"syntology":null},{"paper":null,"slug":"class-interference-regularization","title":"Class Interference Regularization","date":"2020-09-04","arxiv_id":"2009.02396","n_code_links":0,"syntology":null},{"paper":null,"slug":"practical-cross-modal-manifold-alignment-for","title":"Practical Cross-modal Manifold Alignment for Grounded Language","date":"2020-09-01","arxiv_id":"2009.05147","n_code_links":0,"syntology":null},{"paper":"/paper/learning-condition-invariant-features-for","slug":"learning-condition-invariant-features-for","title":"Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images","date":"2020-08-27","arxiv_id":"2008.12165","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-self-supervised-gan-for-unsupervised-few","title":"A Self-supervised GAN for Unsupervised Few-shot Object Recognition","date":"2020-08-16","arxiv_id":"2008.06982","n_code_links":0,"syntology":null},{"paper":"/paper/parameters-sharing-exploration-and-hetero","slug":"parameters-sharing-exploration-and-hetero","title":"Parameter Sharing Exploration and Hetero-Center based Triplet Loss for Visible-Thermal Person Re-Identification","date":"2020-08-14","arxiv_id":"2008.06223","n_code_links":1,"syntology":null},{"paper":null,"slug":"unsupervised-deep-metric-learning-with","title":"Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss","date":"2020-08-10","arxiv_id":"2008.04378","n_code_links":0,"syntology":null}],"record_sha256":"eb754cd4bf05a4fac8a032a29fe183e6584e58adc4f220ac83da746995424773","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}