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Open Vocabulary Semantic Segmentation On 7

Metrics

mIoU

Results

Performance results of various models on this benchmark

		Paper Title	Repository
SILC	25.8	SILC: Improving Vision Language Pretraining with Self-Distillation	-
MaskCLIP++	23.9	High-Quality Mask Tuning Matters for Open-Vocabulary Segmentation
CAT-Seg	23.8	CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
Mask-Adapter	22.7	Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation
SED	22.6	SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation
MAFT+	21.6	Collaborative Vision-Text Representation Optimizing for Open-Vocabulary Segmentation
EBSeg-L	21.0	Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
FC-CLIP	18.2	Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
SCAN	16.7	Open-Vocabulary Segmentation with Semantic-Assisted Calibration
MAFT-ViTL	15.7	Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
ODISE	14.5	Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
OVSeg Swin-B	12.4	Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP
MaskCLIP	10	Open-Vocabulary Universal Image Segmentation with MaskCLIP

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Open Vocabulary Semantic Segmentation On 7 | SOTA | HyperAI