HyperAI
HyperAI
Startseite
Plattform
Dokumentation
Neuigkeiten
Forschungsarbeiten
Tutorials
Datensätze
Wiki
SOTA
LLM-Modelle
GPU-Rangliste
Veranstaltungen
Suche
Über
Nutzungsbedingungen
Datenschutzrichtlinie
Deutsch
HyperAI
HyperAI
Toggle Sidebar
Seite durchsuchen…
⌘
K
Command Palette
Search for a command to run...
Plattform
Startseite
SOTA
Personen-Wiedererkennung
Person Re Identification On Dukemtmc Reid
Person Re Identification On Dukemtmc Reid
Metriken
Rank-1
mAP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Rank-1
mAP
Paper Title
DenseIL
-
97.1
Dense Interaction Learning for Video-based Person Re-identification
CTL Model (ResNet50, 256x128)
95.6
96.1
On the Unreasonable Effectiveness of Centroids in Image Retrieval
BPBreID (RK)
93.9
92.9
Body Part-Based Representation Learning for Occluded Person Re-Identification
Unsupervised Pre-training (ResNet101+RK)
93.99
92.77
Unsupervised Pre-training for Person Re-identification
st-ReID(RE, RK,Cam)
94.5
92.7
Spatial-Temporal Person Re-identification
RGT&RGPR (RK)
94.3
92.7
Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method
Viewpoint-Aware Loss(RK)
93.9
91.8
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification
LDS (ResNet50 + RK)
92.91
91.0
Learning to Disentangle Scenes for Person Re-identification
Adaptive L2 Regularization (with re-ranking)
92.2
90.7
Adaptive L2 Regularization in Person Re-Identification
FlipReID (with re-ranking)
93.0
90.7
FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
DAAF-BoT(RK)
91.7
89.6
Deep Attention Aware Feature Learning for Person Re-Identification
Auto-ReID(RK)
91.4
89.2
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
RPTM
93.5
89.2
Relation Preserving Triplet Mining for Stabilising the Triplet Loss in Re-identification Systems
BoT Baseline(RK)
90.2
89.1
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
st-ReID+InSTD
-
89.1
Learning Instance-level Spatial-Temporal Patterns for Person Re-identification
Top-DB-Net + RK
90.9
88.6
Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification
DG-Net(RK)
90.26
88.31
Joint Discriminative and Generative Learning for Person Re-identification
PyrNet (+ReRank)
90.3
87.7
Aggregating Deep Pyramidal Representations for Person Re-Idenfitication
Deep Constrained Dominant Sets
88.5
86.1
Deep Constrained Dominant Sets for Person Re-identification
Parameter-Free Spatial Attention
89.0
85.9
Parameter-Free Spatial Attention Network for Person Re-Identification
0 of 94 row(s) selected.
Previous
Next
Person Re Identification On Dukemtmc Reid | SOTA | HyperAI