{"work":{"id":"a72dd8f5-38f0-4656-b761-3af761bac9ef","openalex_id":null,"doi":null,"arxiv_id":"1703.07737","raw_key":null,"title":"In Defense of the Triplet Loss for Person Re-Identification","authors":null,"authors_text":"Alexander Hermans, Lucas Beyer, and Bastian Leibe","year":2017,"venue":"cs.CV","abstract":"In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning. The person re-identification subfield is no exception to this. Unfortunately, a prevailing belief in the community seems to be that the triplet loss is inferior to using surrogate losses (classification, verification) followed by a separate metric learning step. We show that, for models trained from scratch as well as pretrained ones, using a variant of the triplet loss to perform end-to-end deep metric learning outperforms most other published methods by a large margin.","external_url":"https://arxiv.org/abs/1703.07737","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-07-04T14:39:57.480607+00:00","pith_arxiv_id":"1703.07737","created_at":"2026-05-09T06:20:41.557903+00:00","updated_at":"2026-07-04T14:39:57.480607+00:00","title_quality_ok":true,"display_title":"In Defense of the Triplet Loss for Person Re-Identification","render_title":"In Defense of the Triplet Loss for Person Re-Identification"},"hub":{"state":{"work_id":"a72dd8f5-38f0-4656-b761-3af761bac9ef","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":38,"external_cited_by_count":null,"distinct_field_count":8,"first_pith_cited_at":"2019-07-02T20:06:21+00:00","last_pith_cited_at":"2026-07-01T18:11:05+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-24T00:49:28.461884+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"method","n":1}],"polarity_counts":[{"context_polarity":"use_method","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}