Papers with Code 아카이브
Interactive Segmentation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Seg-Wild: Interactive Segmentation based on 3D Gaussian Splatting for Unconstrained Image Collections
RAPS-3D: Efficient interactive segmentation for 3D radiological imaging
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
TSDASeg: A Two-Stage Model with Direct Alignment for Interactive Point Cloud Segmentation
SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus
FocalClick-XL: Towards Unified and High-quality Interactive Segmentation
Active-O3: Empowering Multimodal Large Language Models with Active Perception via GRPO
Zero-Shot Gaze-based Volumetric Medical Image Segmentation
TAGS: 3D Tumor-Adaptive Guidance for SAM
iSegMan: Interactive Segment-and-Manipulate 3D Gaussians
MAIS: Memory-Attention for Interactive Segmentation
Benchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive Segmentation
MoSAM: Motion-Guided Segment Anything Model with Spatial-Temporal Memory Selection
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
Easy3D: A Simple Yet Effective Method for 3D Interactive Segmentation
Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge
RefCut: Interactive Segmentation with Reference Guidance
M2N2V2: Multi-Modal Unsupervised and Training-free Interactive Segmentation
ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object
nnInteractive: Redefining 3D Promptable Segmentation
SegAgent: Exploring Pixel Understanding Capabilities in MLLMs by Imitating Human Annotator Trajectories
Continuous Online Adaptation Driven by User Interaction for Medical Image Segmentation
Interactive Segmentation and Report Generation for CT Images
Text-promptable Propagation for Referring Medical Image Sequence Segmentation
Towards Fine-grained Interactive Segmentation in Images and Videos
Segment Anything for Histopathology
Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches
MedicoSAM: Towards foundation models for medical image segmentation
SkipClick: Combining Quick Responses and Low-Level Features for Interactive Segmentation in Winter Sports Contexts
Evidential Calibrated Uncertainty-Guided Interactive Segmentation paradigm for Ultrasound Images
VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation
MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance
TSGaussian: Semantic and Depth-Guided Target-Specific Gaussian Splatting from Sparse Views
SPT: Sequence Prompt Transformer for Interactive Image Segmentation
Lightweight Method for Interactive 3D Medical Image Segmentation with Multi-Round Result Fusion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.