Imagen de Portada

Attention Prompt Tuning: Parameter-efficient Adaptation of Pre-trained Models for Spatiotemporal Modeling

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Bandara, Wele Gedara Chaminda, Patel, Vishal M.
Formato:	Preprint
Publicado:	2024
Materias:	Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
por: Bandara, Wele Gedara Chaminda, et al.
Publicado: (2022)

$\mathsf{CSMAE~}$:~Cataract Surgical Masked Autoencoder (MAE) based Pre-training
por: Shah, Nisarg A., et al.
Publicado: (2025)

$CrowdDiff$: Multi-hypothesis Crowd Density Estimation using Diffusion Models
por: Ranasinghe, Yasiru, et al.
Publicado: (2023)

Stable Diffusion Models are Secretly Good at Visual In-Context Learning
por: Oorloff, Trevine, et al.
Publicado: (2025)

Your Pre-trained Diffusion Model Secretly Knows Restoration
por: Rajagopalan, Sudarshan, et al.
Publicado: (2026)

Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training
por: Lei, Xingliang, et al.
Publicado: (2024)

SDPT: Synchronous Dual Prompt Tuning for Fusion-based Visual-Language Pre-trained Models
por: Zhou, Yang, et al.
Publicado: (2024)

PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning
por: Liu, Xuntao, et al.
Publicado: (2024)

Prompt Your Brain: Scaffold Prompt Tuning for Efficient Adaptation of fMRI Pre-trained Model
por: Dong, Zijian, et al.
Publicado: (2024)

Low-rank Adaptation-based All-Weather Removal for Autonomous Navigation
por: Rajagopalan, Sudarshan, et al.
Publicado: (2024)

Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
por: Wang, Haixin, et al.
Publicado: (2023)

S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
por: Paranjape, Jay N., et al.
Publicado: (2024)

Active Learning for Vision-Language Models
por: Safaei, Bardia, et al.
Publicado: (2024)

Certainty and Uncertainty Guided Active Domain Adaptation
por: Safaei, Bardia, et al.
Publicado: (2025)

ModelMix: A New Model-Mixup Strategy to Minimize Vicinal Risk across Tasks for Few-scribble based Cardiac Segmentation
por: Zhang, Ke, et al.
Publicado: (2024)

MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language Models
por: Miao, Yongzhu, et al.
Publicado: (2023)

Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
por: Ma, Shuailei, et al.
Publicado: (2023)

A Foundation Model for DAS Signal Recognition and Visual Prompt Tuning of the Pre-trained Model for Downstream Tasks
por: Gui, Kun, et al.
Publicado: (2025)

Reducing Bias in Pre-trained Models by Tuning while Penalizing Change
por: Penzel, Niklas, et al.
Publicado: (2024)

Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models
por: Wang, Jifeng, et al.
Publicado: (2024)

RemoteVAR: Autoregressive Visual Modeling for Remote Sensing Change Detection
por: Korkmaz, Yilmaz, et al.
Publicado: (2026)

Data-efficient Event Camera Pre-training via Disentangled Masked Modeling
por: Huang, Zhenpeng, et al.
Publicado: (2024)

Retaining and Enhancing Pre-trained Knowledge in Vision-Language Models with Prompt Ensembling
por: Kim, Donggeun, et al.
Publicado: (2024)

Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness
por: Wang, Sibo, et al.
Publicado: (2024)

Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models
por: Ruan, Shouwei, et al.
Publicado: (2024)

Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models
por: Tang, Yiwen, et al.
Publicado: (2023)

Blackbox Adaptation for Medical Image Segmentation
por: Paranjape, Jay N., et al.
Publicado: (2024)

An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model
por: Tian, Yuxin, et al.
Publicado: (2024)

Skip Tuning: Pre-trained Vision-Language Models are Effective and Efficient Adapters Themselves
por: Wu, Shihan, et al.
Publicado: (2024)

Attention to the Burstiness in Visual Prompt Tuning!
por: Wang, Yuzhu, et al.
Publicado: (2025)

Parameter-efficient Prompt Tuning and Hierarchical Textual Guidance for Few-shot Whole Slide Image Classification
por: Bogahawatte, Jayanie, et al.
Publicado: (2026)

Federated Black-Box Adaptation for Semantic Segmentation
por: Paranjape, Jay N., et al.
Publicado: (2024)

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning
por: Zhu, Haowei, et al.
Publicado: (2024)

Edit2Restore:Few-Shot Image Restoration via Parameter-Efficient Adaptation of Pre-trained Editing Models
por: Yılmaz, M. Akın, et al.
Publicado: (2026)

Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
por: Lu, Feng, et al.
Publicado: (2024)

SelfPrompt: Confidence-Aware Semi-Supervised Tuning for Robust Vision-Language Model Adaptation
por: Roy, Shuvendu, et al.
Publicado: (2025)

AttentionDrag: Exploiting Latent Correlation Knowledge in Pre-trained Diffusion Models for Image Editing
por: Yang, Biao, et al.
Publicado: (2025)

Leveraging the Powerful Attention of a Pre-trained Diffusion Model for Exemplar-based Image Colorization
por: Kosugi, Satoshi
Publicado: (2025)

Face-to-Face: A Video Dataset for Multi-Person Interaction Modeling
por: Chu, Ernie, et al.
Publicado: (2026)

Explicit Uncertainty Modeling for Active CLIP Adaptation with Dual Prompt Tuning
por: Wang, Qian-Wei, et al.
Publicado: (2026)