HyperAI超神経

プラットフォーム

Prompt Engineering On Imagenet R

評価指標

Top-1 accuracy %

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

		Paper Title
POMP	77.9	Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
PromptSRC	77.80	Self-regulating Prompts: Foundational Model Adaptation without Forgetting
MMRL	77.53	MMRL: Multi-Modal Representation Learning for Vision-Language Models
HPT++	77.52	HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
CoPrompt	77.51	Consistency-guided Prompt Learning for Vision-Language Models
HPT	77.38	Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
MaPLe	76.98	MaPLe: Multi-modal Prompt Learning
CoCoOP	76.18	Conditional Prompt Learning for Vision-Language Models
CLIP	73.96	Learning Transferable Visual Models From Natural Language Supervision

0 of 9 row(s) selected.

Prompt Engineering On Imagenet R | SOTA | HyperAI超神経