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SOTA
人员重识别
Person Re Identification On Market 1501
Person Re Identification On Market 1501
评估指标
Rank-1
mAP
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Rank-1
mAP
Paper Title
Unsupervised Pre-training (ResNet101+RK)
-
96.21
Unsupervised Pre-training for Person Re-identification
RGT&RGPR (RK)
96.9
95.6
Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method
SOLIDER (RK)
96.7
95.6
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
st-ReID(RE, RK)
98.0
95.5
Spatial-Temporal Person Re-identification
Viewpoint-Aware Loss(RK)
96.79
95.43
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification
ProNet++ (ResNet50+RK)
96.4
95.3
Rethinking Person Re-identification from a Projection-on-Prototypes Perspective
BPBreID (RK)
96.4
95.3
Body Part-Based Representation Learning for Occluded Person Re-Identification
LightMBN (RR)
96.8
95.3
Lightweight Multi-Branch Network for Person Re-Identification
DAAF-BoT(RK)
96.4
95
Deep Attention Aware Feature Learning for Person Re-Identification
CLIP-ReID+Pose2ID (no RK)
97.3
94.9
From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization
SOLIDER +UFFM+AMC
97
94.9
Enhancing person re-identification via Uncertainty Feature Fusion Method and Auto-weighted Measure Combination
LDS (ResNet50 + RK)
96.17
94.89
Learning to Disentangle Scenes for Person Re-identification
FlipReID (with re-ranking)
95.8
94.7
FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
GNN-Reranking
96.11
94.65
Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective
CA-Jaccard
96.2
94.5
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
Adaptive L2 Regularization (with re-ranking)
96.0
94.4
Adaptive L2 Regularization in Person Re-Identification
BoT Baseline(RK)
95.43
94.24
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
Auto-ReID(RK)
95.4
94.2
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
SSKD(GH)
97.36
94.15
Semi-Supervised Domain Generalizable Person Re-Identification
Top-DB-Net + RK
95.5
94.1
Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification
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HyperAI
HyperAI超神经
首页
算力平台
文档
资讯
论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
服务条款
隐私政策
中文
HyperAI
HyperAI超神经
Toggle Sidebar
全站搜索…
⌘
K
Command Palette
Search for a command to run...
算力平台
首页
SOTA
人员重识别
Person Re Identification On Market 1501
Person Re Identification On Market 1501
评估指标
Rank-1
mAP
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Rank-1
mAP
Paper Title
Unsupervised Pre-training (ResNet101+RK)
-
96.21
Unsupervised Pre-training for Person Re-identification
RGT&RGPR (RK)
96.9
95.6
Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method
SOLIDER (RK)
96.7
95.6
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
st-ReID(RE, RK)
98.0
95.5
Spatial-Temporal Person Re-identification
Viewpoint-Aware Loss(RK)
96.79
95.43
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification
ProNet++ (ResNet50+RK)
96.4
95.3
Rethinking Person Re-identification from a Projection-on-Prototypes Perspective
BPBreID (RK)
96.4
95.3
Body Part-Based Representation Learning for Occluded Person Re-Identification
LightMBN (RR)
96.8
95.3
Lightweight Multi-Branch Network for Person Re-Identification
DAAF-BoT(RK)
96.4
95
Deep Attention Aware Feature Learning for Person Re-Identification
CLIP-ReID+Pose2ID (no RK)
97.3
94.9
From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization
SOLIDER +UFFM+AMC
97
94.9
Enhancing person re-identification via Uncertainty Feature Fusion Method and Auto-weighted Measure Combination
LDS (ResNet50 + RK)
96.17
94.89
Learning to Disentangle Scenes for Person Re-identification
FlipReID (with re-ranking)
95.8
94.7
FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
GNN-Reranking
96.11
94.65
Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective
CA-Jaccard
96.2
94.5
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
Adaptive L2 Regularization (with re-ranking)
96.0
94.4
Adaptive L2 Regularization in Person Re-Identification
BoT Baseline(RK)
95.43
94.24
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
Auto-ReID(RK)
95.4
94.2
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
SSKD(GH)
97.36
94.15
Semi-Supervised Domain Generalizable Person Re-Identification
Top-DB-Net + RK
95.5
94.1
Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification
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Person Re Identification On Market 1501 | SOTA | HyperAI超神经