HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Out-of-Distribution Detection
Out Of Distribution Detection On Imagenet 1K 8
Out Of Distribution Detection On Imagenet 1K 8
Metrics
AUROC
FPR95
Results
Performance results of various models on this benchmark
Columns
Model Name
AUROC
FPR95
Paper Title
DOE
76.26
80.94
Out-of-distribution Detection with Implicit Outlier Transformation
RP+GradNorm
-
73.53
Detecting Out-of-distribution Data through In-distribution Class Prior
KNN (ResNet-50)
80.10
69.53
Out-of-Distribution Detection with Deep Nearest Neighbors
DML
-
57.40
Decoupling MaxLogit for Out-of-Distribution Detection
SHE
-
54.19
Out-of-Distribution Detection based on In-Distribution Data Patterns Memorization with Modern Hopfield Energy
ODIN+UMAP (ResNet-50)
86.92
49.69
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
KNN (ResNet-50 SupCon)
88.40
48.91
Out-of-Distribution Detection with Deep Nearest Neighbors
ReAct (ResNet-50)
88.16
47.69
ReAct: Out-of-distribution Detection With Rectified Activations
GradNorm (ResNetv2-101)
-
46.48
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
NPOS
90.44
43.77
Non-Parametric Outlier Synthesis
MOS (BiT-S-R101x1)
92.01
40.63
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
MCM (CLIP-B)
92.57
37.59
Delving into Out-of-Distribution Detection with Vision-Language Representations
DICE (ResNet-50)
90.83
35.15
DICE: Leveraging Sparsification for Out-of-Distribution Detection
RankFeat (ResNetv2-101)
94.07
29.27
RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection
MCM (CLIP-L)
94.14
29.00
Delving into Out-of-Distribution Detection with Vision-Language Representations
ASH-S (ResNet-50)
94.02
27.98
Extremely Simple Activation Shaping for Out-of-Distribution Detection
DICE + ReAct (ResNet-50)
93.94
25.45
DICE: Leveraging Sparsification for Out-of-Distribution Detection
SCALE (ResNet50)
95.02
23.27
Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
NNGuide (RegNet)
94.43
21.58
Nearest Neighbor Guidance for Out-of-Distribution Detection
LINe (ResNet50)
95.26
19.48
LINe: Out-of-Distribution Detection by Leveraging Important Neurons
0 of 21 row(s) selected.
Previous
Next
Out Of Distribution Detection On Imagenet 1K 8 | SOTA | HyperAI