Metric Learning On Cub 200 2011

Metrics

R@1

Results

Performance results of various models on this benchmark

		Paper Title	Repository
Unicom+ViT-L@336px	90.1	Unicom: Universal and Compact Representation Learning for Image Retrieval
EfficientDML-VPTSP-G/512	88.5	Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
Hyp-ViT	85.6	Hyperbolic Vision Transformers: Combining Improvements in Metric Learning
NED	74.9	Calibrated neighborhood aware confidence measure for deep metric learning	-
CCL (ResNet-50)	73.45	Center Contrastive Loss for Metric Learning	-
ResNet-50 + AVSL	71.9	Attributable Visual Similarity Learning
ResNet-50 + Intra-Batch Connections	71.8	Learning Intra-Batch Connections for Deep Metric Learning
ResNet50 + Language	71.4	Integrating Language Guidance into Vision-based Deep Metric Learning
ResNet-50 + Metrix	71.4	It Takes Two to Tango: Mixup for Deep Metric Learning
BN-Inception + Proxy-Anchor	71.1	Proxy Anchor Loss for Deep Metric Learning
ResNet50 + NIR	70.5	Non-isotropy Regularization for Proxy-based Deep Metric Learning
ResNet50 + S2SD	70.1	S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
ResNet-50 + Cross-Entropy	69.2	A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses
ResNet50 + DiVA	69.2	DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
ResNet-50 + ProxyNCA++	69.0	ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
MS + DIML	68.15	Towards Interpretable Deep Metric Learning with Structural Matching
ResNet50 (128) + PADS	67.3	PADS: Policy-Adapted Sampling for Visual Similarity Learning
ABE + HORDE	66.8	Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings
ResNet50 (128) + MIC	66.1	MIC: Mining Interclass Characteristics for Improved Metric Learning
BN-Inception + Group Loss	65.5	The Group Loss for Deep Metric Learning

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Metric Learning On Cub 200 2011

Metrics

Results