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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 61–70 of 127 papers

TitleStatusHype
DegustaBot: Zero-Shot Visual Preference Estimation for Personalized Multi-Object Rearrangement—0
Rethinking Visual Prompting for Multimodal Large Language Models with External Knowledge—0
Robust Adaptation of Foundation Models with Black-Box Visual Prompting—0
Towards Open-World Grasping with Large Vision-Language Models—0
Dynamic Domains, Dynamic Solutions: DPCore for Continual Test-Time AdaptationCode1
RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics—0
OT-VP: Optimal Transport-guided Visual Prompting for Test-Time AdaptationCode1
Exploring the Zero-Shot Capabilities of Vision-Language Models for Improving Gaze Following—0
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language ModelsCode2
Learning Visual Prompts for Guiding the Attention of Vision Transformers—0
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