Label Anything (Vit-B/16-SAM)

Reported on 3 benchmarks across 3 tasks · 1 paper · 3 SOTA

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

Methodology2 results

Few-Shot LearningonCOCO-20i (2-way 1-shot)
mIoU· uses extra data· 2024-07-02
34.6
SOTA
Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts arXiv:2407.02075
Meta-LearningonCOCO-20i (2-way 1-shot)
mIoU· uses extra data· 2024-07-02
34.6
SOTA
Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts arXiv:2407.02075

Computer Vision1 result

Few-Shot Semantic SegmentationonCOCO-20i (2-way 1-shot)
mIoU· uses extra data· 2024-07-02
34.6
SOTA
Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts arXiv:2407.02075