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SOTA
Prompt Engineering
Prompt Engineering On Ucf101
Prompt Engineering On Ucf101
평가 지표
Harmonic mean
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Harmonic mean
Paper Title
Repository
PromptKD
86.10
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
MetaPrompt
81.35
Learning Domain Invariant Prompt for Vision-Language Models
MaPLe
80.82
MaPLe: Multi-modal Prompt Learning
PromptSRC
82.74
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
HPT
83.16
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
MMRL
83.89
MMRL: Multi-Modal Representation Learning for Vision-Language Models
CoPrompt
83.07
Consistency-guided Prompt Learning for Vision-Language Models
ProMetaR
83.25
Prompt Learning via Meta-Regularization
CLIP
73.85
Learning Transferable Visual Models From Natural Language Supervision
HPT++
83.81
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
CoCoOp
77.64
Conditional Prompt Learning for Vision-Language Models
RPO
79.34
Read-only Prompt Optimization for Vision-Language Few-shot Learning
DePT
82.46
DePT: Decoupled Prompt Tuning
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