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Models/VLTSeg

VLTSeg

Reported on 6 benchmarks across 4 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical2 results

Semantic SegmentationonCityscapes test
Mean IoU (class)· 2023-12-04
86.4
SOTA
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021
Semantic SegmentationonBDD100K val
mIoU· 2023-12-04
72.5
SOTA
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021

Audio2 results

10-shot image generationonCityscapes test
Mean IoU (class)· 2023-12-04
86.4
SOTA
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021
10-shot image generationonBDD100K val
mIoU· 2023-12-04
72.5
SOTA
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021

Methodology1 result

Domain AdaptationonGTA-to-Avg(Cityscapes,BDD,Mapillary)
mIoU· 2023-12-04
63.5
best: 4489 (Self-adaptation (ResNet - 101))
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021

Computer Vision1 result

Domain GeneralizationonGTA-to-Avg(Cityscapes,BDD,Mapillary)
mIoU· 2023-12-04
63.5
best: 4489 (Self-adaptation (ResNet - 101))
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning arXiv:2312.02021