Papers with Code 아카이브

Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

29

평가표

150

보존된 평가 기록

1,918

코드

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

https://github.com/raun1/ASC-NET

공식 코드

ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly Segmentation

https://github.com/raun1/Complementary_Segmentation_Network

공식 코드

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/rauschecker-sugrue-labs/kspace-segmentation

공식 코드

Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputs

https://github.com/ravishah1/dcin-cqg

공식 코드

Color-Quality Invariance for Robust Medical Image Segmentation

https://github.com/rayguan97/GANav-offroad

공식 코드

GANav: Efficient Terrain Segmentation for Robot Navigation in Unstructured Outdoor Environments

https://github.com/rayleizhu/biformer

공식 코드

BiFormer: Vision Transformer with Bi-Level Routing Attention

https://github.com/rayleizhu/glmix

공식 코드

Revisiting the Integration of Convolution and Attention for Vision Backbone

https://github.com/raymondwang987/nvds

공식 코드

NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation

https://github.com/raymondyeh07/learnable_polyphase_sampling

공식 코드

Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

https://github.com/raywu0123/Brain-Tumor-Segmentation

공식 코드

Deep Learning Based Segmentation of Various Brain Lesions for Radiosurgery

https://github.com/razeineldin/DeepSeg

공식 코드

DeepSeg: Deep Neural Network Framework for Automatic Brain Tumor Segmentation using Magnetic Resonance FLAIR Images

https://github.com/rb-sl/expertdrivennuclei

공식 코드

An expert-driven data generation pipeline for histological images

https://github.com/rb080/wss_pole

공식 코드

Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation

https://github.com/rd20karim/M2T-Segmentation

공식 코드

Motion2Language, unsupervised learning of synchronized semantic motion segmentation

https://github.com/rdlin118/hilots

공식 코드

HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving

https://github.com/ready2drop/DTS

공식 코드

Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer

https://github.com/reafly/semimedseg

공식 코드

Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation

https://github.com/realwecan/mju-waste

공식 코드

A Multi-Level Approach to Waste Object Segmentation

https://github.com/reasat/mstt

공식 코드

MSTT-199: MRI Dataset for Musculoskeletal Soft Tissue Tumor Segmentation

https://github.com/redabensaidds/foundation_fewshot

공식 코드

A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models

https://github.com/rederoth/aiconic_scandy

공식 코드

A Robotics-Inspired Scanpath Model Reveals the Importance of Uncertainty and Semantic Object Cues for Gaze Guidance in Dynamic Scenes

https://github.com/redlessme/transmission-bvm

공식 코드

Transmission-Guided Bayesian Generative Model for Smoke Segmentation

https://github.com/reeive/rehydil

공식 코드

Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing Modalities

https://github.com/rehg-lab/dope_selfsup

공식 코드

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

https://github.com/remcoroyen/vx-s3dis

공식 코드

RESSCAL3D++: Joint Acquisition and Semantic Segmentation of 3D Point Clouds

https://github.com/renato145/posthocOS

공식 코드

Post-hoc Overall Survival Time Prediction from Brain MRI

https://github.com/renmengye/imageqa-public

공식 코드

Exploring Models and Data for Image Question Answering

https://github.com/restor-foundation/tcd

공식 코드

OAM-TCD: A globally diverse dataset of high-resolution tree cover maps

https://github.com/retis-ai/semsegadvpatch

공식 코드

On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving

https://github.com/reza-nasirigerdeh/norm-torch

공식 코드

Kernel Normalized Convolutional Networks

https://github.com/rezaqorbani/semla

공식 코드

Semantic Library Adaptation: LoRA Retrieval and Fusion for Open-Vocabulary Semantic Segmentation

https://github.com/rezazad68/BCDU-Net

공식 코드

Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions

https://github.com/rezazad68/deep-intervertebral-disc-labeling

공식 코드

Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling

https://github.com/rezazad68/fewshot-segmentation

공식 코드

On the Texture Bias for Few-Shot CNN Segmentation

https://github.com/rezazad68/smunet

공식 코드

SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalities

https://github.com/rezazad68/tmunet

공식 코드

Contextual Attention Network: Transformer Meets U-Net

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