Cover Image

DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ren, Li, Chen, Chen, Wang, Liqiang, Hua, Kien
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
by: Ren, Li, et al.
Published: (2024)

PRO-VPT: Distribution-Adaptive Visual Prompt Tuning via Prompt Relocation
by: Shang, Chikai, et al.
Published: (2025)

iVPT: Improving Task-relevant Information Sharing in Visual Prompt Tuning by Cross-layer Dynamic Connection
by: Zhou, Nan, et al.
Published: (2024)

Towards Improved Proxy-based Deep Metric Learning via Data-Augmented Domain Adaptation
by: Ren, Li, et al.
Published: (2024)

NeRF-VPT: Learning Novel View Representations with Neural Radiance Fields via View Prompt Tuning
by: Chen, Linsheng, et al.
Published: (2024)

SemPT: Semantic Prompt Tuning for Vision-Language Models
by: Shi, Xiao, et al.
Published: (2025)

Learning Visual Prompts for Guiding the Attention of Vision Transformers
by: Rezaei, Razieh, et al.
Published: (2024)

Do Vision-Language Transformers Exhibit Visual Commonsense? An Empirical Study of VCR
by: Li, Zhenyang, et al.
Published: (2024)

MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model
by: Wang, Xinyang, et al.
Published: (2024)

Robust Prompt Tuning for Vision-Language Models with Mild Semantic Noise
by: Gao, Yansheng, et al.
Published: (2025)

Visual Variational Autoencoder Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)

AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors
by: Chang, You-Ming, et al.
Published: (2023)

FVG-PT: Adaptive Foreground View-Guided Prompt Tuning for Vision-Language Models
by: Li, Haoyang, et al.
Published: (2026)

Robust Visual Localization via Semantic-Guided Multi-Scale Transformer
by: Tian, Zhongtao, et al.
Published: (2025)

Efficient Test-Time Prompt Tuning for Vision-Language Models
by: Zhu, Yuhan, et al.
Published: (2024)

SDVPT: Semantic-Driven Visual Prompt Tuning for Open-World Object Counting
by: Zhao, Yiming, et al.
Published: (2025)

ArGue: Attribute-Guided Prompt Tuning for Vision-Language Models
by: Tian, Xinyu, et al.
Published: (2023)

Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models
by: Li, Jiayu, et al.
Published: (2026)

From Boundaries to Semantics: Prompt-Guided Multi-Task Learning for Petrographic Thin-section Segmentation
by: Ren, Yili, et al.
Published: (2026)

TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models
by: Wang, Xin, et al.
Published: (2024)

PromptMoE: Generalizable Zero-Shot Anomaly Detection via Visually-Guided Prompt Mixtures
by: Shao, Yuheng, et al.
Published: (2025)

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

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

LION: Implicit Vision Prompt Tuning
by: Wang, Haixin, et al.
Published: (2023)

Progressive Semantic-Guided Vision Transformer for Zero-Shot Learning
by: Chen, Shiming, et al.
Published: (2024)

FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
by: Singha, Mainak, et al.
Published: (2025)

Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers
by: Yashwanth, M, et al.
Published: (2025)

ADAPT to Robustify Prompt Tuning Vision Transformers
by: Eskandar, Masih, et al.
Published: (2024)

Joint Post-Training Quantization of Vision Transformers with Learned Prompt-Guided Data Generation
by: Li, Shile, et al.
Published: (2026)

A Visual Semantic Adaptive Watermark grounded by Prefix-Tuning for Large Vision-Language Model
by: Zheng, Qi, et al.
Published: (2026)

Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models
by: Hai, Jia-Wei, et al.
Published: (2026)

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models
by: Wang, Xin, et al.
Published: (2026)

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models
by: Zhai, Kun, et al.
Published: (2025)

Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformers
by: Xu, Gangwei, et al.
Published: (2025)

Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts
by: Wang, Yubin, et al.
Published: (2025)

Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models
by: Liu, Xinyang, et al.
Published: (2023)

CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
by: Gong, Ziyang, et al.
Published: (2024)

Multi-dimensional Visual Prompt Enhanced Image Restoration via Mamba-Transformer Aggregation
by: Jiang, Aiwen, et al.
Published: (2024)

Panther: Illuminate the Sight of Multimodal LLMs with Instruction-Guided Visual Prompts
by: Li, Honglin, et al.
Published: (2024)

Visual Instance-aware Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)