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プラットフォーム
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SOTA
リアルタイムセマンティックセグメンテーション
Real Time Semantic Segmentation On Cityscapes
Real Time Semantic Segmentation On Cityscapes
評価指標
Frame (fps)
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
Frame (fps)
mIoU
Paper Title
PIDNet-L
31.1(3090)
80.6%
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
SFNet-R18
25.7(1080Ti)
80.4%
Semantic Flow for Fast and Accurate Scene Parsing
PIDNet-M
42.2(3090)
79.8%
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
PIDNet-S
93.2(3090)
78.6%
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
RegSeg (no ImageNet pretraining)
30
78.3%
Rethinking Dilated Convolution for Real-time Semantic Segmentation
PP-LiteSeg-B2
102.6(1080Ti)
77.5%
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
DDRNet-23-slim
101.6(2080Ti)
77.4%
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
STDC2-75
97.0(1080Ti)
76.8%
Rethinking BiSeNet For Real-time Semantic Segmentation
SwinMTL
-
76.41%
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera Images
HyperSeg-M
36.9
75.8%
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation
SwiftNetRN-18
39.9
75.5%
In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images
BiSeNet V2-Large
47.3
75.3%
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
STDC1-75
126.7
75.3%
Rethinking BiSeNet For Real-time Semantic Segmentation
TD4-BISE18
47.6 (Titan X)
74.9%
Temporally Distributed Networks for Fast Video Semantic Segmentation
PP-LiteSeg-T2
143.6(1080Ti)
74.9%
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
ShelfNet18
59.2
74.8%
ShelfNet for Fast Semantic Segmentation
BiSeNet(ResNet-18)
65.5
74.7%
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
BiSeNet
65.5
74.7%
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
PP-LiteSeg-B1
195.3(1080Ti)
73.9%
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
SegBlocks-RN18 (t=0.4)
48.6 (1080Ti)
73.8%
SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time Segmentation
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Real Time Semantic Segmentation On Cityscapes | SOTA | HyperAI超神経