Papers with Code 아카이브

Segmentation

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코드

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

https://github.com/imatge-upc/synthref

공식 코드

SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation

https://github.com/imesluh/vocalfolds

공식 코드

A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation

https://github.com/imop-lab/defn-pytorch

공식 코드

DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Indistinct-Boundary Object Segmentation

https://github.com/impl-lab/ial

공식 코드

How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation

https://github.com/importzl/blo-sam

공식 코드

BLO-SAM: Bi-level Optimization Based Overfitting-Preventing Finetuning of SAM

https://github.com/importzl/semantic_segmentation

공식 코드

Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimes

https://github.com/imran-maia/ibsr_18_bratseg_deep_learning

공식 코드

Comparative Study of Probabilistic Atlas and Deep Learning Approaches for Automatic Brain Tissue Segmentation from MRI Using N4 Bias Field Correction and Anisotropic Diffusion Pre-processing Techniques

https://github.com/imsy-dkfz/htc

공식 코드

Robust deep learning-based semantic organ segmentation in hyperspectral images

https://github.com/instanseg/instanseg

공식 코드

InstanSeg: an embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentation

https://github.com/intcomp/camouflaged-vlm

공식 코드

Open-Vocabulary Camouflaged Object Segmentation with Cascaded Vision Language Models

https://github.com/intra3d2019/IntrA

공식 코드

IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning

https://github.com/intrepidChw/ASAP-Net

공식 코드

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

https://github.com/ipis-xielei/cntseg

공식 코드

An Arbitrary-Modal Fusion Network for Volumetric Cranial Nerves Tract Segmentation

https://github.com/ipmi-nwu/helpnet

공식 코드

HELPNet: Hierarchical Perturbations Consistency and Entropy-guided Ensemble for Scribble Supervised Medical Image Segmentation

https://github.com/irikos/rip_currents

공식 코드

Rip Current Segmentation: A Novel Benchmark and YOLOv8 Baseline Results

https://github.com/irmvlab/sfcnet

공식 코드

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation

https://github.com/isee-laboratory/cvpr24_atba

공식 코드

Efficient and Effective Weakly-Supervised Action Segmentation via Action-Transition-Aware Boundary Alignment

https://github.com/isi-vista/structure_via_consensus

공식 코드

Towards Learning Structure via Consensus for Face Segmentation and Parsing

https://github.com/isl-org/lang-seg

공식 코드

Language-driven Semantic Segmentation

https://github.com/ismailelbouknify/ct-xcov

공식 코드

CT-xCOV: a CT-scan based Explainable Framework for COVid-19 diagnosis

https://github.com/isunchy/3d_instance_segmentation

공식 코드

Semantic Segmentation-Assisted Instance Feature Fusion for Multi-Level 3D Part Instance Segmentation

https://github.com/isunchy/semi_supervised_3d_segmentation

공식 코드

Semi-supervised 3D shape segmentation with multilevel consistency and part substitution

https://github.com/itmo-mmrm-lab/cellpose

공식 코드

Cellpose+, a morphological analysis tool for feature extraction of stained cell images

https://github.com/itruonghai/segtransvae

공식 코드

SegTransVAE: Hybrid CNN -- Transformer with Regularization for medical image segmentation

https://github.com/itschenyu/aecif-net

공식 코드

Attention-Enhanced Co-Interactive Fusion Network (AECIF-Net) for Automated Structural Condition Assessment in Visual Inspection

https://github.com/itschenyu/multitask-learning-bridge-inspection

공식 코드

A Multitask Deep Learning Model for Parsing Bridge Elements and Segmenting Defect in Bridge Inspection Images

https://github.com/itsowen/betternet

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BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp Segmentation

https://github.com/ituvisionlab/Uncertainty-Based-Dynamic-Graph-Neighborhoods

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Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation

https://github.com/ivadomed/model_seg_gm-wm_t2star_7t_unet3d-multiclass

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2D Multi-Class Model for Gray and White Matter Segmentation of the Cervical Spinal Cord at 7T

https://github.com/ivezakis/effisegnet

공식 코드

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder

https://github.com/ivmcl/pacavit

공식 코드

PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers

https://github.com/ivust/one-shot-texture-segmentation

공식 코드

One-shot Texture Segmentation

https://github.com/iweisskohl/evidence-fusion-with-contextual-discounting

공식 코드

Evidence fusion with contextual discounting for multi-modality medical image segmentation

https://github.com/ixilai/samf

공식 코드

SAMF: Small-Area-Aware Multi-focus Image Fusion for Object Detection

https://github.com/j-morano/mirage

공식 코드

MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis

https://github.com/j-morano/multimodal-fusion-fpn

공식 코드

Deep Multimodal Fusion of Data with Heterogeneous Dimensionality via Projective Networks

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