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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 71–80 of 127 papers

TitleStatusHype
Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling—0
IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual PromptingCode0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Query Efficient Black-Box Visual Prompting with Subspace Learning—0
Visual Prompting with Iterative Refinement for Design Critique Generation—0
Test-time Correction with Human Feedback: An Online 3D Detection System via Visual Prompting—0
MLLM-Search: A Zero-Shot Approach to Finding People using Multimodal Large Language Models—0
Prompting the Unseen: Detecting Hidden Backdoors in Black-Box Models—0
WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning—0
Benchmarking Human and Automated Prompting in the Segment Anything ModelCode0
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