Open Vocabulary Semantic Segmentation On 2

Metrics

mIoU

Results

Performance results of various models on this benchmark

		Paper Title
Mask-Adapter	38.2	Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation
MaskCLIP++	38.2	High-Quality Mask Tuning Matters for Open-Vocabulary Segmentation
CAT-Seg	37.9	CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
SILC	37.7	SILC: Improving Vision Language Pretraining with Self-Distillation
MAFT+	36.1	Collaborative Vision-Text Representation Optimizing for Open-Vocabulary Segmentation
OVSeg + OpenDAS	35.8	OpenDAS: Open-Vocabulary Domain Adaptation for 2D and 3D Segmentation
SED	35.2	SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation
CLIPSelf	34.5	CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
FC-CLIP	34.1	Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
SCAN	33.5	Open-Vocabulary Segmentation with Semantic-Assisted Calibration
EBSeg-L	32.8	Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
MAFT-ViTL	32.0	Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
PACL	31.4	Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning
ODISE	29.9	Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
OVSeg Swin-B	29.6	Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP
MaskCLIP	23.7	Open-Vocabulary Universal Image Segmentation with MaskCLIP
POMP	20.7	-
SimSeg	20.5	A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model
TTD (TCL)	17.0	TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
LaVG	15.8	In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

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Open Vocabulary Semantic Segmentation On 2

Metrics

Results