HyperAI
Home
News
Latest Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
English
HyperAI
Toggle sidebar
Search the site…
⌘
K
Home
SOTA
Semantic Segmentation
Semantic Segmentation On Nighttime Driving
Semantic Segmentation On Nighttime Driving
Metrics
mIoU
Results
Performance results of various models on this benchmark
Columns
Model Name
mIoU
Paper Title
Repository
DANNet (RefineNet)
42.36
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
Refign (DAFormer)
56.8
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
DANNet (DeepLab-v2)
44.98
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
TADP
60.8
Text-image Alignment for Diffusion-based Perception
CoDA
59.2
CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
CIConv
41.6
Zero-Shot Day-Night Domain Adaptation with a Physics Prior
DMAda
36.1
Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime
-
Refign (HRDA)
58.0
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
ERF-PSPNet
45.09
See Clearer at Night: Towards Robust Nighttime Semantic Segmentation through Day-Night Image Conversion
-
MGCDA
49.4
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation
GCMA
45.6
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation
DANNet (PSPNet)
47.70
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
0 of 12 row(s) selected.
Previous
Next