Papers Interactive Segmentation
“Interactive Segmentation” 태그가 달린 논문 305편 · 필터 해제
From Few-Shot Segmentation to Clinician-in-the-Loop Medical Image Analysis
Few-shot medical image segmentation (FSMIS) seeks to delineate unseen structures from a small support set, but its standard formulation fixes task-defining evidence before inference. This assumption is fragile when query…
Medical Image SegmentationInteractive SegmentationTest-time AdaptationPrompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CT
Accurate segmentation of interstitial lung disease (ILD) patterns is essential for quantitative disease assessment and longitudinal monitoring. However, existing approaches remain limited by relying on dense annotations …
Interactive SegmentationPrompt-Conditioned Channel Attention for Hierarchical Feature Modulation toward Anatomy-Agnostic Segmentation
Anatomically plausible segmentation remains challenging because of low contrast, ambiguous boundaries, and modality-specific artifacts. Interactive segmentation has emerged as a promising strategy to guide feature extrac…
Medical Image SegmentationInteractive SegmentationUniMedSeg: Unified In-Context Learning for Multi-Paradigm 2D/3D Medical Image Segmentation
Medical image segmentation foundation models are expected to generalize across diverse clinical scenarios, yet existing universal methods remain fragmented by prompt paradigms and spatial dimensions. Visual in-context le…
Medical Image SegmentationInteractive SegmentationOnline Segment 3D Gaussians via Launching Virtual Drones
Interactive segmentation of 3D Gaussians offers a compelling opportunity for real-time manipulation of 3D scenes, thanks to the real-time rendering capability of 3D Gaussian Splatting (3DGS). However, existing methods re…
Interactive SegmentationPGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation
Segment Anything Model (SAM) has revolutionized promptable image segmentation with strong zero-shot generalization. However, its performance degrades substantially under real-world imaging artifacts such as noise, blur, …
Zero-shot GeneralizationInteractive SegmentationImage SegmentationTemporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection
Accurately localizing and segmenting small targets in low signal-to-noise ratio (SNR) infrared sequences remains a challenging task. Since targets are often indistinguishable from the background in individual frames, exi…
Interactive SegmentationPrompting Diffusion Models for Zero-Shot Instance Segmentation
Several disruptive research directions have recently emerged in computer vision, including foundation models achieving previously unseen zero-shot performance in scene understanding, even interactively, and generative mo…
Interactive SegmentationInstance SegmentationScene UnderstandingHuman-in-the-Loop Atlas-Based 3D Asset Segmentation for Interactive Content Workflows
Segmenting 3D assets into meaningful regions remains challenging, especially when segmentation criteria are application-dependent and require user control. We present a human-in-the-loop pipeline for generating a segment…
Interactive SegmentationStyle TransferOne Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation
Cell instance segmentation models trained on cell-specific datasets suffer severe performance drops on out-of-distribution cell types, while interactive foundation models overcome this through per-instance prompting at a…
Interactive SegmentationInstance SegmentationCLIP-Guided SAM: Parameter-Efficient Semantic Conditioning for Promptable Segmentation
Promptable foundation models such as the Segment Anything Model (SAM) produce high-quality masks but remain semantically blind, relying on external prompts to specify categories. Existing vision-language approaches addre…
Interactive SegmentationSILSM: A Sustainable Interactive Level Set Method for Progressive Refinement
Interactive segmentation aims to precisely isolate target objects using sparse user guidance. However, traditional methods often suffer from heavy interaction burdens and parameter sensitivity, while deep learning approa…
Interactive SegmentationClickSeg3D: Few-Click Interactive Segmentation via Semantic Embeddings
Interactive segmentation allows efficient label generation by leveraging user-provided clicks to progressively refine predictions, which is critical when fully supervised labels are costly or generalization to unseen cla…
Interactive 3D Instance SegmentationInteractive SegmentationMedP-CLIP: Medical CLIP with Region-Aware Prompt Integration
Contrastive Language-Image Pre-training (CLIP) has demonstrated outstanding performance in global image understanding and zero-shot transfer through large-scale text-image alignment. However, the core of medical image an…
Interactive SegmentationFrom Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks
Visual in-context learning models are designed to adapt to new tasks by leveraging a set of example input-output pairs, enabling rapid generalization without task-specific fine-tuning. However, these models operate in a …
Interactive SegmentationPose EstimationPC-SAM: Patch-Constrained Fine-Grained Interactive Road Segmentation in High-Resolution Remote Sensing Images
Road masks obtained from remote sensing images effectively support a wide range of downstream tasks. In recent years, most studies have focused on improving the performance of fully automatic segmentation models for this…
Interactive SegmentationRoad SegmentationClore: Interactive Pathology Image Segmentation with Click-based Local Refinement
Recent advancements in deep learning-based interactive segmentation methods have significantly improved pathology image segmentation. Most existing approaches utilize user-provided positive and negative clicks to guide t…
Interactive SegmentationImage SegmentationMagicSeg: Open-World Segmentation Pretraining via Counterfactural Diffusion-Based Auto-Generation
Open-world semantic segmentation presently relies significantly on extensive image-text pair datasets, which often suffer from a lack of fine-grained pixel annotations on sufficient categories. The acquisition of such da…
Interactive SegmentationSemantic SegmentationImage GenerationSpeak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery
We introduce a speech-guided embodied agent framework for video-guided skull base surgery that dynamically executes perception and image-guidance tasks in response to surgeon queries. The proposed system integrates natur…
Interactive SegmentationActiveFreq: Integrating Active Learning and Frequency Domain Analysis for Interactive Segmentation
Interactive segmentation is commonly used in medical image analysis to obtain precise, pixel-level labeling, typically involving iterative user input to correct mislabeled regions. However, existing approaches often fail…
Interactive SegmentationActive Learning