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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 101–125 of 127 papers

TitleStatusHype
Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4VCode4
Unifying Image Processing as Visual Prompting Question Answering—0
AutoVP: An Automated Visual Prompting Framework and BenchmarkCode1
VPA: Fully Test-Time Visual Prompt Adaptation—0
Uncovering the Hidden Cost of Model CompressionCode0
ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation—0
Visual Instruction Inversion: Image Editing via Visual PromptingCode1
Fast Segment AnythingCode0
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image UnderstandingCode0
Fine-Grained Visual PromptingCode1
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual PromptingCode0
Explicit Visual Prompting for Universal Foreground SegmentationsCode2
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation—0
UPGPT: Universal Diffusion Model for Person Image Generation, Editing and Pose TransferCode1
Segment AnythingCode5
Learning Expressive Prompting With Residuals for Vision Transformers—0
BlackVIP: Black-Box Visual Prompting for Robust Transfer LearningCode1
Exploring the Benefits of Visual Prompting in Differential PrivacyCode0
Explicit Visual Prompting for Low-Level Structure SegmentationsCode2
Diversity-Aware Meta Visual PromptingCode1
Text-Visual Prompting for Efficient 2D Temporal Video GroundingCode1
Unleashing the Power of Visual Prompting At the Pixel LevelCode0
Understanding and Improving Visual Prompting: A Label-Mapping PerspectiveCode1
Visual Prompting for Adversarial RobustnessCode1
FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training—0
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