HyperAI超神经
首页
资讯
最新论文
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
中文
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
首页
SOTA
Person Re Identification
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
Repository
CAL
95.5
89.5
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Auto-ReID(RK)
95.4
94.2
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
OSNet
94.8
84.9
Omni-Scale Feature Learning for Person Re-Identification
Top-DB-Net + RK
95.5
94.1
Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification
BPBreID
95.7
89.4
Body Part-Based Representation Learning for Occluded Person Re-Identification
DAAF-BoT
95.1
87.9
Deep Attention Aware Feature Learning for Person Re-Identification
S-CNN
65.88
39.55
Gated Siamese Convolutional Neural Network Architecture for Human Re-Identification
-
MGN + CircleLoss(ours)
96.1
87.4
Circle Loss: A Unified Perspective of Pair Similarity Optimization
A3M
86.54
68.97
Attribute-Aware Attention Model for Fine-grained Representation Learning
P2-Net (triplet loss)
95.2
85.6
Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
PyrNet (single-shot)
93.6
81.7
Aggregating Deep Pyramidal Representations for Person Re-Idenfitication
SPreID [kalayeh2018human]
93.6
83.3
Human Semantic Parsing for Person Re-identification
-
CBN+BoT*
94.3
83.6
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization
CLIP-ReID Baseline +UFFM+AMC
96.1
92.0
Enhancing Person Re-Identification via Uncertainty Feature Fusion and Auto-weighted Measure Combination
-
IDE*
85.66
65.87
Camera Style Adaptation for Person Re-identification
LuNet
81.38
60.71
In Defense of the Triplet Loss for Person Re-Identification
Dual Cluster Contrastive
95.4
89.2
Dual Cluster Contrastive learning for Object Re-Identification
MSINet (2.3M w/o RK)
95.3
89.6
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
DiP (without RK)
95.8
90.8
DiP: Learning Discriminative Implicit Parts for Person Re-Identification
KPR
95.9
89.6
Keypoint Promptable Re-Identification
0 of 135 row(s) selected.
Previous
Next