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Fishyscapes L&F
Anomaly Detection on Fishyscapes L&F
Metric: FPR95 (higher is better)
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Date (oldest first)
Model name (A→Z)
#
Model
↕
FPR95
▼
Augmentations
Paper
Date
↕
Code
1
Dirichlet DeepLab
47.43
Yes
The Fishyscapes Benchmark: Measuring Blind Spots...
2019-04-05
Code
2
Softmax Entropy
44.8
No
The Fishyscapes Benchmark: Measuring Blind Spots...
2019-04-05
Code
3
Bayesian DeepLab
38.5
No
The Fishyscapes Benchmark: Measuring Blind Spots...
2019-04-05
Code
4
Learned Embedding Density
24.4
Yes
The Fishyscapes Benchmark: Measuring Blind Spots...
2019-04-05
Code
5
Void Classifier
22.11
Yes
The Fishyscapes Benchmark: Measuring Blind Spots...
2019-04-05
Code
6
OutlierHead combined instances
19.02
No
Simultaneous Semantic Segmentation and Outlier D...
2019-08-03
Code
7
SynBoost
15.79
Yes
Pixel-wise Anomaly Detection in Complex Driving ...
2021-03-09
Code
8
SML
14.53
No
Standardized Max Logits: A Simple yet Effective ...
2021-07-23
Code
9
CosMe
13.32
No
Consensus Synergizes with Memory: A Simple Appro...
2021-11-24
-
10
cDNP
8.9
No
Far Away in the Deep Space: Dense Nearest-Neighb...
2022-11-12
Code
11
PEBAL
7.58
Yes
Pixel-wise Energy-biased Abstention Learning for...
2021-11-24
Code
12
cDNP+OE
7.5
Yes
Far Away in the Deep Space: Dense Nearest-Neighb...
2022-11-12
Code
13
DenseHybrid
6.2
Yes
DenseHybrid: Hybrid Anomaly Detection for Dense ...
2022-07-06
Code
14
FlowEneDet
5.2
No
Concurrent Misclassification and Out-of-Distribu...
2023-05-16
Code
15
Mask2Anomaly
4.36
Yes
Unmasking Anomalies in Road-Scene Segmentation
2023-07-25
Code
16
RPL+CoroCL
2.27
Yes
Residual Pattern Learning for Pixel-wise Out-of-...
2022-11-26
Code
17
NFlowJS-GF (with extra inlier set: Vistas and Wilddash2)
2
Yes
Dense Out-of-Distribution Detection by Robust Le...
2021-12-23
-
#1
Dirichlet DeepLab
SOTA
47.43
FPR95
· Augmentations
· 2019-04-05
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Code
#2
Softmax Entropy
44.8
FPR95
· 2019-04-05
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Code
#3
Bayesian DeepLab
38.5
FPR95
· 2019-04-05
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Code
#4
Learned Embedding Density
24.4
FPR95
· Augmentations
· 2019-04-05
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Code
#5
Void Classifier
22.11
FPR95
· Augmentations
· 2019-04-05
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Code
#6
OutlierHead combined instances
19.02
FPR95
· 2019-08-03
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift
Code
#7
SynBoost
15.79
FPR95
· Augmentations
· 2021-03-09
Pixel-wise Anomaly Detection in Complex Driving Scenes
Code
#8
SML
14.53
FPR95
· 2021-07-23
Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation
Code
#9
CosMe
13.32
FPR95
· 2021-11-24
Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes
#10
cDNP
8.9
FPR95
· 2022-11-12
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detection
Code
#11
PEBAL
7.58
FPR95
· Augmentations
· 2021-11-24
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
Code
#12
cDNP+OE
7.5
FPR95
· Augmentations
· 2022-11-12
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detection
Code
#13
DenseHybrid
6.2
FPR95
· Augmentations
· 2022-07-06
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition
Code
#14
FlowEneDet
5.2
FPR95
· 2023-05-16
Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow
Code
#15
Mask2Anomaly
4.36
FPR95
· Augmentations
· 2023-07-25
Unmasking Anomalies in Road-Scene Segmentation
Code
#16
RPL+CoroCL
2.27
FPR95
· Augmentations
· 2022-11-26
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
Code
#17
NFlowJS-GF (with extra inlier set: Vistas and Wilddash2)
2
FPR95
· Augmentations
· 2021-12-23
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data