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/OpenMask3D/openmask3d

공식 코드

OpenMask3D: Open-Vocabulary 3D Instance Segmentation

https://github.com/OpenRobotLab/Grounded_3D-LLM

공식 코드

Grounded 3D-LLM with Referent Tokens

https://github.com/PJLallen/InstanceSAM2Eval

공식 코드

Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation

https://github.com/PKU-YuanGroup/LLMBind

공식 코드

LLMBind: A Unified Modality-Task Integration Framework

https://github.com/POSTECH-CVLab/InstaOrder

공식 코드

Instance-wise Occlusion and Depth Orders in Natural Scenes

https://github.com/PRBonn/semantic-kitti-api

공식 코드

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

https://github.com/PaddlePaddle/PaddleClas

공식 코드

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

https://github.com/PaddlePaddle/PaddleOCR

공식 코드

SVTR: Scene Text Recognition with a Single Visual Model

https://github.com/PaddlePaddle/PaddleSeg

공식 코드

GINet: Graph Interaction Network for Scene Parsing

https://github.com/ParitoshParmar/HalluciNet

공식 코드

HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN

https://github.com/Pay20Y/GCAN

공식 코드

Gaussian Constrained Attention Network for Scene Text Recognition

https://github.com/Pay20Y/SEED

공식 코드

SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition

https://github.com/PeikeLi/Self-Correction-Human-Parsing

공식 코드

Self-Correction for Human Parsing

https://github.com/PengyiZhang/ACCL

공식 코드

ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation

https://github.com/PengyiZhang/SlimYOLOv3

공식 코드

SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications

https://github.com/PerForm-Lab-RIT/domain-adaptation-eye-tracking

공식 코드

Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking Systems

https://github.com/PkuRainBow/OCNet

공식 코드

OCNet: Object Context Network for Scene Parsing

https://github.com/PkuRainBow/OCNet.pytorch

공식 코드

OCNet: Object Context Network for Scene Parsing

https://github.com/Pointcept/OpenIns3D

공식 코드

OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation

https://github.com/Powertony102/corn_official

공식 코드

Leveraging CORAL-Correlation Consistency Network for Semi-Supervised Left Atrium MRI Segmentation

https://github.com/PramaLLC/BEN

공식 코드

BEN: Using Confidence-Guided Matting for Dichotomous Image Segmentation

https://github.com/Prof-Pratik-Shah-Lab-UCI/skin_project_2024

공식 코드

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions

https://github.com/Project-MONAI/VISTA

공식 코드

VISTA3D: Versatile Imaging SegmenTation and Annotation model for 3D Computed Tomography

https://github.com/Project-MONAI/research-contributions/tree/master/SwinUNETR/BRATS21

공식 코드

Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images

https://github.com/Project-MONAI/research-contributions/tree/master/UNETR/BTCV

공식 코드

UNETR: Transformers for 3D Medical Image Segmentation

https://github.com/Project-MONAI/tutorials/tree/master/automl/DiNTS

공식 코드

DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation

https://github.com/Purushothaman-natarajan/VALE-Explainer

공식 코드

VALE: A Multimodal Visual and Language Explanation Framework for Image Classifiers using eXplainable AI and Language Models

https://github.com/PythonOT/POT/blob/master/ot/da.py

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Optimal Transport for Multi-source Domain Adaptation under Target Shift

https://github.com/QIU023/SATS_Continual_Semantic_Seg

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SATS: Self-Attention Transfer for Continual Semantic Segmentation

https://github.com/QQTh4/NAS4Ultrasound

공식 코드

SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image Segmentation

https://github.com/Qi-Zhangyang/GPT4Scene

공식 코드

GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

https://github.com/QiZhangsama/P-MSDiff

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P-MSDiff: Parallel Multi-Scale Diffusion for Remote Sensing Image Segmentation

https://github.com/QianWangX/VidSeg_diffusion

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Zero-Shot Video Semantic Segmentation based on Pre-Trained Diffusion Models

https://github.com/Qianyu1226/Crosslink-Net

공식 코드

Crosslink-Net: Double-branch Encoder Segmentation Network via Fusing Vertical and Horizontal Convolutions

https://github.com/Qiming-Huang/ssformer

공식 코드

Stepwise Feature Fusion: Local Guides Global

https://github.com/QingtaoPan/DuSSS

공식 코드

DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image Segmentation

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