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Semantic Segmentation On Pascal Voc 2012 Val
Semantic Segmentation On Pascal Voc 2012 Val
評価指標
mIoU
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
mIoU
Paper Title
Repository
DeepLabv3-JFT
82.7%
Rethinking Atrous Convolution for Semantic Image Segmentation
RRM
66.3
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
FastDenseNas-arch1
77.1%
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
SID
-
Simple Does It: Weakly Supervised Instance and Semantic Segmentation
-
SpineNet-S143 (single-scale test)
85.64%
Dilated SpineNet for Semantic Segmentation
-
FastDenseNas-arch2
77.3%
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
PRM
53.4%
Weakly Supervised Instance Segmentation using Class Peak Response
Auto-DeepLab-L
82.04%
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
HyperSeg-L
80.61%
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation
SSDD
64.9
Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation
PSA w/ EADER DeepLab (Xception-65)
62.8%
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation
FastDenseNas-arch0
78.0%
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
ReLICv2
77.9%
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
Eff-B7 NAS-FPN (Copy-Paste pre-training, single-scale))
86.6%
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
BYOL
75.7%
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
SIW
65%
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings
-
G2
55.7%
Exploiting saliency for object segmentation from image level labels
-
DetCon
77.3%
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
DeepLabv3 (ImageNet+300M)
76.5%
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
TADP
87.11%
Text-image Alignment for Diffusion-based Perception
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