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Interactive Segmentation

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하위 태스크

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평가표

14

보존된 평가 기록

74

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/leon2000-ai/tsgaussian

공식 코드

TSGaussian: Semantic and Depth-Guided Target-Specific Gaussian Splatting from Sparse Views

https://github.com/lids-unicamp/rethinking-interactive-image-segmentation

공식 코드

Rethinking Interactive Image Segmentation: Feature Space Annotation

https://github.com/lik1996/icmformer

공식 코드

Interactive Image Segmentation with Cross-Modality Vision Transformers

https://github.com/lxtgh/omg-seg

공식 코드

OMG-Seg: Is One Model Good Enough For All Segmentation?

https://github.com/mamrehn/interactive_image_segmentation_evaluation

공식 코드

A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems

https://github.com/masadcv/MONet-MONAILabel

공식 코드

Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation

https://github.com/masadcv/econet-monailabel

공식 코드

ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation

https://github.com/masadcv/fastgeodis

공식 코드

FastGeodis: Fast Generalised Geodesic Distance Transform

https://github.com/masadcv/pytorchhaarfeatures

공식 코드

ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation

https://github.com/matt3o/autopet2-submission

공식 코드

Sliding Window FastEdit: A Framework for Lesion Annotation in Whole-body PET Images

https://github.com/mazurowski-lab/sam-texturalconfusion-metrics

공식 코드

Quantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast Objects

https://github.com/mazurowski-lab/segment-anything-medical

공식 코드

Segment Anything Model for Medical Image Analysis: an Experimental Study

https://github.com/mazurowski-lab/segment-anything-medical-evaluation

공식 코드

Segment Anything Model for Medical Image Analysis: an Experimental Study

https://github.com/medicinetoken/medical-sam2

공식 코드

Medical SAM 2: Segment medical images as video via Segment Anything Model 2

https://github.com/medicl-vu/prism

공식 코드

PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts

https://github.com/medicl-vu/prism-placenta

공식 코드

Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images

https://github.com/medicl-vu/variability

공식 코드

Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts

https://github.com/mic-dkfz/napari-nninteractive

공식 코드

nnInteractive: Redefining 3D Promptable Segmentation

https://github.com/mic-dkfz/nninteractive

공식 코드

nnInteractive: Redefining 3D Promptable Segmentation

https://github.com/microsoft/SoM

공식 코드

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

https://github.com/navidstuv/NuClick

공식 코드

NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy Images

https://github.com/ollie-ztz/continue_tuning

공식 코드

Leveraging AI Predicted and Expert Revised Annotations in Interactive Segmentation: Continual Tuning or Full Training?

https://github.com/philippendres/CellPilot

공식 코드

CellPilot

https://github.com/project-monai/monailabel

공식 코드

DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images

https://github.com/sabarim/itis

공식 코드

Iteratively Trained Interactive Segmentation

https://github.com/scaelles/DEXTR-KerasTensorflow

공식 코드

Deep Extreme Cut: From Extreme Points to Object Segmentation

https://github.com/scaelles/DEXTR-PyTorch

공식 코드

Deep Extreme Cut: From Extreme Points to Object Segmentation

https://github.com/schorob/skipclick

공식 코드

SkipClick: Combining Quick Responses and Low-Level Features for Interactive Segmentation in Winter Sports Contexts

https://github.com/schorob/wseseg

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WSESeg: Introducing a Dataset for the Segmentation of Winter Sports Equipment with a Baseline for Interactive Segmentation

https://github.com/segments-ai/latent-diffusion-segmentation

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A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting

https://github.com/shanzard/ros-sam

공식 코드

ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object

https://github.com/shawnchenn/flexiblereflectionremoval

공식 코드

FIRM: Flexible Interactive Reflection reMoval

https://github.com/shelhamer/revolver

공식 코드

Few-Shot Segmentation Propagation with Guided Networks

https://github.com/stanley-313/imagesegfm-survey

공식 코드

Image Segmentation in Foundation Model Era: A Survey

https://github.com/sudraj2002/fsgrasp

공식 코드

Remote Task-oriented Grasp Area Teaching By Non-Experts through Interactive Segmentation and Few-Shot Learning

https://github.com/sugar0725/seg-wild

공식 코드

Seg-Wild: Interactive Segmentation based on 3D Gaussian Splatting for Unconstrained Image Collections

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.