Papers Visual Prompt Tuning
“Visual Prompt Tuning” 태그가 달린 논문 88편 · 필터 해제
Multitask Vision-Language Prompt Tuning
Prompt Tuning, conditioning on task-specific learned prompt vectors, has emerged as a data-efficient and parameter-efficient method for adapting large pretrained vision-language models to multiple downstream tasks. Howev…
Visual Prompt TuningUnified Vision and Language Prompt Learning
Prompt tuning, a parameter- and data-efficient transfer learning paradigm that tunes only a small number of parameters in a model's input space, has become a trend in the vision community since the emergence of large vis…
Domain GeneralizationFew-Shot LearningPrompt LearningTransfer Learning+1Visual Prompt Tuning for Test-time Domain Adaptation
Models should be able to adapt to unseen data during test-time to avoid performance drops caused by inevitable distribution shifts in real-world deployment scenarios. In this work, we tackle the practical yet challenging…
Domain AdaptationTest-time AdaptationUnsupervised Domain AdaptationVisual Prompt TuningVisual Prompt Tuning for Generative Transfer Learning
Transferring knowledge from an image synthesis model trained on a large dataset is a promising direction for learning generative image models from various domains efficiently. While previous works have studied GAN models…
Image GenerationTransfer LearningVisual Prompt TuningVisual Prompt Tuning for Few-Shot Text Classification
Deploying large-scale pre-trained models in the prompt-tuning paradigm has demonstrated promising performance in few-shot learning. Particularly, vision-language pre-training models (VL-PTMs) have been intensively explor…
ClassificationFew-Shot LearningFew-Shot Text Classificationimage-classification+4Prompt-Matched Semantic Segmentation
The objective of this work is to explore how to effectively and efficiently adapt pre-trained visual foundation models to various downstream tasks of semantic segmentation. Previous methods usually fine-tuned the entire …
Prompt LearningRepresentation LearningSegmentationSemantic Segmentation+1Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model
With the emergence of large pre-trained vison-language model like CLIP, transferable representations can be adapted to a wide range of downstream tasks via prompt tuning. Prompt tuning tries to probe the beneficial infor…
General KnowledgeLanguage ModellingVisual Prompt TuningVisual Prompt Tuning
The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie, full fine-tuning. This paper introduces Visual Prompt Tuning (VPT) as an efficient and effective alternative to…
Image ClassificationLong-tail LearningPrompt EngineeringVisual Prompt Tuning