Browse State-of-the-Art › Unsupervised Vehicle Re-Identification
Unsupervised Vehicle Re-Identification
8 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
8 shown of 8 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
17 Nov 2023 1 repository listed Syntology ran 5 of 10 samples · 5 unverifiedIn particular, Jaccard distance calculates the distance based on the overlap of relevant neighbors.
-
26 Oct 2023 1 repository listedAlthough prompt learning has enabled a recent work named CLIP-ReID to achieve promising performance, the underlying mechanisms and the necessity of prompt learning remain unclear due to the absence of semantic labels in…
-
19 Oct 2023 1 repository listedThe fast improvement of deep learning methods resulted in breakthroughs in image classification, object detection, and object tracking.
-
11 Feb 2023 1 repository listedWith the large-scale and dynamic road environment, the paradigm of supervised vehicle re-identification shows limited scalability because of the heavy reliance on large-scale annotated datasets.
-
23 Jan 2023 1 repository listedTo address this problem, in this paper, we propose a simple Triplet Contrastive Representation Learning (TCRL) framework which leverages cluster features to bridge the part features and global features for unsupervised…
-
28 Mar 2022 1 repository listed Syntology ran 4 of 5 samples · 1 unverifiedIn this paper, we propose a novel Part-based Pseudo Label Refinement (PPLR) framework that reduces the label noise by employing the complementary relationship between global and part features.
-
14 Sep 2021 1 repository listedHowever, this achievement requires large-scale and well-annotated datasets.
-
3 Mar 2021 1 repository listedThe results of DPLM are applied to dictionary-based triplet loss (DTL) to improve the discriminativeness of learnt features and to refine the quality of the results of DPLM progressively.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections