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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 1–25 of 127 papers

TitleStatusHype
Stepwise Decomposition and Dual-stream Focus: A Novel Approach for Training-free Camouflaged Object SegmentationCode0
RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought—0
Grid-LOGAT: Grid Based Local and Global Area Transcription for Video Question Answering—0
DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models—0
A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis—0
VP Lab: a PEFT-Enabled Visual Prompting Laboratory for Semantic Segmentation—0
Vision Graph Prompting via Semantic Low-Rank DecompositionCode1
Token Coordinated Prompt Attention is Needed for Visual PromptingCode1
Zoomer: Adaptive Image Focus Optimization for Black-box MLLM—0
Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models—0
RadSAM: Segmenting 3D radiological images with a 2D promptable model—0
Visual and textual prompts for enhancing emotion recognition in video—0
NVSMask3D: Hard Visual Prompting with Camera Pose Interpolation for 3D Open Vocabulary Instance Segmentation—0
Visual Prompting for One-shot Controllable Video Editing without Inversion—0
EarthGPT-X: Enabling MLLMs to Flexibly and Comprehensively Understand Multi-Source Remote Sensing Imagery—0
Prompt-Guided Attention Head Selection for Focus-Oriented Image Retrieval—0
Is Temporal Prompting All We Need For Limited Labeled Action Recognition?—0
Towards Online Multi-Modal Social Interaction UnderstandingCode0
VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis—0
3DAxisPrompt: Promoting the 3D Grounding and Reasoning in GPT-4o—0
KUDA: Keypoints to Unify Dynamics Learning and Visual Prompting for Open-Vocabulary Robotic Manipulation—0
Chameleon: Fast-slow Neuro-symbolic Lane Topology ExtractionCode2
Towards Universal Text-driven CT Image SegmentationCode0
Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth AmbiguityCode0
The Role of Background Information in Reducing Object Hallucination in Vision-Language Models: Insights from Cutoff API Prompting—0
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