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Visual Prompting

Visual Prompting is the task of streamlining computer vision processes by harnessing the power of prompts, inspired by the breakthroughs of text prompting in NLP. This innovative approach involves using a few visual prompts to swiftly convert an unlabeled dataset into a deployed model, significantly reducing development time for both individual projects and enterprise solutions.

Papers

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Showing 76–100 of 127 papers

TitleStatusHype
Cycle-Consistency Uncertainty Estimation for Visual Prompting based One-Shot Defect Segmentation—0
DegustaBot: Zero-Shot Visual Preference Estimation for Personalized Multi-Object Rearrangement—0
DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models—0
EarthGPT-X: Enabling MLLMs to Flexibly and Comprehensively Understand Multi-Source Remote Sensing Imagery—0
End-to-end Open-vocabulary Video Visual Relationship Detection using Multi-modal Prompting—0
Explore until Confident: Efficient Exploration for Embodied Question Answering—0
Exploring the Zero-Shot Capabilities of Vision-Language Models for Improving Gaze Following—0
Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms—0
From PowerPoint UI Sketches to Web-Based Applications: Pattern-Driven Code Generation for GIS Dashboard Development Using Knowledge-Augmented LLMs, Context-Aware Visual Prompting, and the React Framework—0
FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training—0
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation—0
Grid-LOGAT: Grid Based Local and Global Area Transcription for Video Question Answering—0
GSON: A Group-based Social Navigation Framework with Large Multimodal Model—0
ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation—0
Is Temporal Prompting All We Need For Limited Labeled Action Recognition?—0
KUDA: Keypoints to Unify Dynamics Learning and Visual Prompting for Open-Vocabulary Robotic Manipulation—0
LaViP:Language-Grounded Visual Prompts—0
Learning Expressive Prompting With Residuals for Vision Transformers—0
Learning Visual Prompts for Guiding the Attention of Vision Transformers—0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation—0
MLLM-Search: A Zero-Shot Approach to Finding People using Multimodal Large Language Models—0
MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting—0
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks—0
NVSMask3D: Hard Visual Prompting with Camera Pose Interpolation for 3D Open Vocabulary Instance Segmentation—0
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