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Semantic Segmentation
Semantic Segmentation On Camvid
Semantic Segmentation On Camvid
Metrics
Mean IoU
Results
Performance results of various models on this benchmark
Columns
Model Name
Mean IoU
Paper Title
Repository
RTFormer-Base
82.5
RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer
-
EDANet
66.4
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation
-
DenseDecoder
70.9
Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation
-
LMDNet
63.5
Efficient Road Lane Marking Detection with Deep Learning
-
DSNet-Base
83.32
DSNet: A Novel Way to Use Atrous Convolutions in Semantic Segmentation
-
ETC-Mobile
76.3
Efficient Semantic Video Segmentation with Per-frame Inference
-
Template-Based NAS-arch1 (480x360 inputs)
63.2%
Template-Based Automatic Search of Compact Semantic Segmentation Architectures
-
DeepLabV3Plus + SDCNetAug
81.7%
Improving Semantic Segmentation via Video Propagation and Label Relaxation
-
DDRNet23
80.6%
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
-
DeepLab-MSc-CRF-LargeFOV
61.6%
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
-
PIDNet-Wider
82.0%
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
-
VideoGCRF
75.2
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation
-
Template-Based NAS-arch0 (480x360 inputs)
63.9%
Template-Based Automatic Search of Compact Semantic Segmentation Architectures
-
SegNet
46.4%
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
-
DFANet A
64.7%
DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
-
Dilated Convolutions
65.3%
Multi-Scale Context Aggregation by Dilated Convolutions
-
SIW
83.7
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings
-
SERNet-Former
84.62
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks
-
FC-DenseNet103
66.9%
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
-
BiSeNet
68.7%
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
-
0 of 21 row(s) selected.
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