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
中文
HyperAI
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
Command Palette
Search for a command to run...
首页
SOTA
人脸验证
Face Verification On Ijb C
Face Verification On Ijb C
评估指标
TAR @ FAR=1e-3
TAR @ FAR=1e-4
TAR @ FAR=1e-5
model
training dataset
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
TAR @ FAR=1e-3
TAR @ FAR=1e-4
TAR @ FAR=1e-5
model
training dataset
Paper Title
Repository
Partial FC
-
98.00%
97.23%
ViT-L
WebFace42M
Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC
PartialFC
-
97.97%
96.93%
R200
WebFace42M
Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC
WebFace42M baseline
-
97.7%
-
R100
WebFace42M
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
-
AdaFace (WebFace4M)
-
97.39%
-
-
-
AdaFace: Quality Adaptive Margin for Face Recognition
FFC
-
97.31%
-
R100
WebFace42M
An Efficient Training Approach for Very Large Scale Face Recognition
CAFace+AdaFace (WebFace4M)
98.08
97.3%
-
-
-
Cluster and Aggregate: Face Recognition with Large Probe Set
AdaFace (MS1MV3)
-
97.09%
-
-
-
AdaFace: Quality Adaptive Margin for Face Recognition
AdaFace (MS1MV2)
-
96.89%
-
-
-
AdaFace: Quality Adaptive Margin for Face Recognition
ElasticFace-Cos
-
96.57%
-
R100
MS1M V2
ElasticFace: Elastic Margin Loss for Deep Face Recognition
Cos+UNPG
97.57
96.38%
94.47%
R100
MS1MV2
Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
Arc+UNPG
97.51
96.33%
-
-
-
Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
QMagFace
97.62
96.19%
-
-
-
QMagFace: Simple and Accurate Quality-Aware Face Recognition
CurricularFace
-
96.1%
-
-
-
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition
MagFace++
-
95.97%
90.36%
R100
MS1MV2
MagFace: A Universal Representation for Face Recognition and Quality Assessment
ArcFace+CSFM
-
95.9%
94.06%
-
-
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
HeadSharing: SH-KD
-
95.64%
93.73%
MobileFaceNet
MS1M V3
It's All in the Head: Representation Knowledge Distillation through Classifier Sharing
L2E+IS-sampling
97.05%
95.49%
93.25%
MobileFaceNet
MS1M V3
Rectifying the Data Bias in Knowledge Distillation
-
HeadSharing: TH-KD
-
95.48%
93.50%
MobileFaceNet
MS1M V3
It's All in the Head: Representation Knowledge Distillation through Classifier Sharing
circle loss
96.29%
93.95%
89.60%
R100
MS1M Cleaned
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Mag+UNPG
-
-
94.7%
-
-
Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
0 of 26 row(s) selected.
Previous
Next
Face Verification On Ijb C | SOTA | HyperAI超神经