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/ortonwang/pcdal

공식 코드

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification

https://github.com/ortonwang/plgdf

공식 코드

Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation

https://github.com/ortonwang/scribblevs

공식 코드

ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection

https://github.com/oskarnatan/deepipcv2

공식 코드

DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle

https://github.com/osupcvlab/mobileunetr

공식 코드

MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation

https://github.com/osupcvlab/segformer3d

공식 코드

SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation

https://github.com/othmanela/certified_segmentation

공식 코드

Towards Better Certified Segmentation via Diffusion Models

https://github.com/othmanela/medical_cert_seg

공식 코드

Certification of Deep Learning Models for Medical Image Segmentation

https://github.com/oulu-imeds/log-vmamba

공식 코드

LoG-VMamba: Local-Global Vision Mamba for Medical Image Segmentation

https://github.com/oulu-imeds/sauna

공식 코드

Image-level Regression for Uncertainty-aware Retinal Image Segmentation

https://github.com/oulu-imeds/singr

공식 코드

SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression

https://github.com/ownstyledu/Translate-to-Recognize-Networks

공식 코드

Translate-to-Recognize Networks for RGB-D Scene Recognition

https://github.com/ozan-oktay/Attention-Gated-Networks

공식 코드

Attention U-Net: Learning Where to Look for the Pancreas

https://github.com/pablohc97/TFM

공식 코드

Neural Networks with Divisive normalization for image segmentation with application in cityscapes dataset

https://github.com/palaashagrawal/stupd

공식 코드

STUPD: A Synthetic Dataset for Spatial and Temporal Relation Reasoning

https://github.com/palmdong/smmcl

공식 코드

Understanding Dark Scenes by Contrasting Multi-Modal Observations

https://github.com/pandapan01/evssc

공식 코드

Event-aided Semantic Scene Completion

https://github.com/panlingua/multilingual-tst-datasets

공식 코드

Multilingual Text Style Transfer: Datasets & Models for Indian Languages

https://github.com/pansanity666/INO_VOS

공식 코드

In-N-Out Generative Learning for Dense Unsupervised Video Segmentation

https://github.com/pascalcpp/sdcl

공식 코드

SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation

https://github.com/pashtari/deconver

공식 코드

Deconver: A Deconvolutional Network for Medical Image Segmentation

https://github.com/pashtari/factorizer

공식 코드

Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation

https://github.com/pathak22/ccnn

공식 코드

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

https://github.com/patrick-knab/dseg-lime

공식 코드

Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation Models

https://github.com/paulcouairon/diffcut

공식 코드

DiffCut: Catalyzing Zero-Shot Semantic Segmentation with Diffusion Features and Recursive Normalized Cut

https://github.com/paulgay/VGfM

공식 코드

Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning

https://github.com/pavliclab/aaai2022-clear2022-visual_relationship_detection-rwfn

공식 코드

Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship Detection

https://github.com/pay20y/pimnet

공식 코드

PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition

https://github.com/pbizopoulos/comprehensive-comparison-of-deep-learning-models-for-lung-and-covid-19-lesion-segmentation-in-ct

공식 코드

Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scans

https://github.com/pcasolab/vdst-net

공식 코드

Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video

https://github.com/pemami4911/segregate-relate-imagine

공식 코드

Towards Improving the Generation Quality of Autoregressive Slot VAEs

https://github.com/penaud-polge/fully-trainable-gaussian-derivative-layer

공식 코드

Fully trainable Gaussian derivative convolutional layer

https://github.com/pengchengshi1220/nextou

공식 코드

NexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation

https://github.com/pengchihan/binaryimagedownsampling

공식 코드

Topology-Preserving Downsampling of Binary Images

https://github.com/pengtaojiang/tsp6k

공식 코드

Traffic Scene Parsing through the TSP6K Dataset

https://github.com/perceptioncomputinglab/instance2022

공식 코드

The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge

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