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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 51–75 of 127 papers

TitleStatusHype
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image UnderstandingCode0
Exploring the Benefits of Visual Prompting in Differential PrivacyCode0
UICrit: Enhancing Automated Design Evaluation with a UICritique DatasetCode0
Stepwise Decomposition and Dual-stream Focus: A Novel Approach for Training-free Camouflaged Object SegmentationCode0
When Does Visual Prompting Outperform Linear Probing for Vision-Language Models? A Likelihood PerspectiveCode0
Unleashing the Power of Visual Prompting At the Pixel LevelCode0
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual PromptingCode0
ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual PromptsCode0
Uncovering the Hidden Cost of Model CompressionCode0
Targeted Visual Prompting for Medical Visual Question AnsweringCode0
Towards Online Multi-Modal Social Interaction UnderstandingCode0
Benchmarking Human and Automated Prompting in the Segment Anything ModelCode0
VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis—0
WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning—0
Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model—0
Zoomer: Adaptive Image Focus Optimization for Black-box MLLM—0
3DAxiesPrompts: Unleashing the 3D Spatial Task Capabilities of GPT-4V—0
3DAxisPrompt: Promoting the 3D Grounding and Reasoning in GPT-4o—0
A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis—0
Affordance-Guided Reinforcement Learning via Visual Prompting—0
Analogist: Out-of-the-box Visual In-Context Learning with Image Diffusion Model—0
Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling—0
Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models—0
BLINK: Multimodal Large Language Models Can See but Not Perceive—0
Chat2Layout: Interactive 3D Furniture Layout with a Multimodal LLM—0
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