Papers with Code 아카이브

2D Semantic Segmentation

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하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/cheng-01037/probability_calibration_for_ood_mri_segmentation

공식 코드

Improved post-hoc probability calibration for out-of-domain MRI segmentation

https://github.com/chenguolin/InstructScene

공식 코드

InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior

https://github.com/chengyinlee/autoprosam_2024

공식 코드

AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation

https://github.com/chengyinlee/focalunetr

공식 코드

FocalUNETR: A Focal Transformer for Boundary-aware Segmentation of CT Images

https://github.com/chengyinlee/mulmodseg_2024

공식 코드

MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training

https://github.com/chengzhag/DeepPanoContext

공식 코드

DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization

https://github.com/chengzhag/Implicit3DUnderstanding

공식 코드

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

https://github.com/chenhong-zhou/OM-Net

공식 코드

One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor Segmentation

https://github.com/chenhongruixuan/bright

공식 코드

BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response

https://github.com/chenhongruixuan/mambacd

공식 코드

ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model

https://github.com/chenjzbuaa/satir

공식 코드

Learning to "Segment Anything" in Thermal Infrared Images through Knowledge Distillation with a Large Scale Dataset SATIR

https://github.com/chenxi116/TF-phrasecut-public

공식 코드

Recurrent Multimodal Interaction for Referring Image Segmentation

https://github.com/cherise215/CardiacMRSegmentation

공식 코드

Improving the generalizability of convolutional neural network-based segmentation on CMR images

https://github.com/cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation

공식 코드

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

https://github.com/cherise215/advchain

공식 코드

Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation

https://github.com/cherise215/maxstyle

공식 코드

MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation

https://github.com/chikap421/mseg_vcuq

공식 코드

MSEG-VCUQ: Multimodal SEGmentation with Enhanced Vision Foundation Models, Convolutional Neural Networks, and Uncertainty Quantification for High-Speed Video Phase Detection Data

https://github.com/chikap421/videosam

공식 코드

VideoSAM: A Large Vision Foundation Model for High-Speed Video Segmentation

https://github.com/chilab1/dnn-parser

공식 코드

IODeep: an IOD for the introduction of deep learning in the DICOM standard

https://github.com/chilab1/iodeep

공식 코드

IODeep: an IOD for the introduction of deep learning in the DICOM standard

https://github.com/choi58/mtcm

공식 코드

Multi-Context Temporal Consistent Modeling for Referring Video Object Segmentation

https://github.com/chongqingnosubway/selfreg-unet

공식 코드

SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation

https://github.com/choyingw/SCADC-DepthCompletion

공식 코드

Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

https://github.com/chrissyinreallife/kneesegmentwithsam

공식 코드

Segmentation by registration-enabled SAM prompt engineering using five reference images

https://github.com/christophreich1996/yeast-in-microstructures-dataset

공식 코드

An Instance Segmentation Dataset of Yeast Cells in Microstructures

https://github.com/chungmin99/garfield

공식 코드

GARField: Group Anything with Radiance Fields

https://github.com/chuyun-shen/sam_2_medical_3d

공식 코드

Interactive 3D Medical Image Segmentation with SAM 2

https://github.com/chy-upc/abd

공식 코드

Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation

https://github.com/ciampluca/diffusion_semi_supervised_biomedical_image_segmentation

공식 코드

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

https://github.com/cianmscannell/da_cmr

공식 코드

Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation

https://github.com/cilinyan/VISA

공식 코드

VISA: Reasoning Video Object Segmentation via Large Language Models

https://github.com/cilinyan/revos-api

공식 코드

VISA: Reasoning Video Object Segmentation via Large Language Models

https://github.com/cindyxinyiwang/deep-latent-sequence-model

공식 코드

A Probabilistic Formulation of Unsupervised Text Style Transfer

https://github.com/cistib/DDIR

공식 코드

Joint segmentation and discontinuity-preserving deformable registration: Application to cardiac cine-MR images

https://github.com/cityu-aim-group/jcas

공식 코드

Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels

https://github.com/cjlee94/points2image

공식 코드

Microscopy Image Segmentation via Point and Shape Regularized Data Synthesis

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