HyperAI
HyperAI
الرئيسية
الأخبار
أحدث الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
العربية
HyperAI
HyperAI
Toggle sidebar
البحث في الموقع...
⌘
K
الرئيسية
SOTA
التمييز الدلالي
Semantic Segmentation On Cityscapes
Semantic Segmentation On Cityscapes
المقاييس
Mean IoU (class)
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Mean IoU (class)
Paper Title
Repository
ESANet-R34-NBt1D
80.09%
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
-
ESNet
70.7%
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation
ResNeSt200 (Mapillary)
83.3%
ResNeSt: Split-Attention Networks
DUC-HDC (ResNet-101)
77.6%
Understanding Convolution for Semantic Segmentation
LightSeg-DarkNet19
70.75%
LiteSeg: A Novel Lightweight ConvNet for Semantic Segmentation
AdapNet++
81.24%
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation
HRNetV2 + OCR (w/ ASP)
83.7%
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
ShelfNet-34
79.0%
ShelfNet for Fast Semantic Segmentation
DeepLabv3 (ResNet-101, coarse)
81.3%
Rethinking Atrous Convolution for Semantic Image Segmentation
InternImage-H
86.1%
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
SqueezeNAS (LAT Large)
72.5%
SqueezeNAS: Fast neural architecture search for faster semantic segmentation
OCNet
81.7%
OCNet: Object Context Network for Scene Parsing
MRFM(coarse)
83.0%
Multi Receptive Field Network for Semantic Segmentation
-
LiteSeg-MobileNet
67.81%
LiteSeg: A Novel Lightweight ConvNet for Semantic Segmentation
HRNetV2 (train+val)
81.6%
Deep High-Resolution Representation Learning for Visual Recognition
ESPNetv2
66.2%
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
LightSeg-MobileNet
67.81%
LiteSeg: A Novel Lightweight ConvNet for Semantic Segmentation
DPN
66.8%
Semantic Image Segmentation via Deep Parsing Network
SPNet (ResNet-101)
82.0%
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
HRNet (HRNetV2-W48)
81.6%
High-Resolution Representations for Labeling Pixels and Regions
0 of 105 row(s) selected.
Previous
Next
Semantic Segmentation On Cityscapes | SOTA | HyperAI