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Segmentation

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

https://github.com/longmalongma/desa2va

공식 코드

Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder

https://github.com/longyin880815/STCNN

공식 코드

Spatiotemporal CNN for Video Object Segmentation

https://github.com/looking9218/reliablereseg

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Reliable Joint Segmentation of Retinal Edema Lesions in OCT Images

https://github.com/looooongChen/instance_segmentation_with_pixel_embeddings

공식 코드

Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints

https://github.com/looooongchen/sortedap

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SortedAP: Rethinking evaluation metrics for instance segmentation

https://github.com/lorebianchi98/Talk2DINO

공식 코드

Talking to DINO: Bridging Self-Supervised Vision Backbones with Language for Open-Vocabulary Segmentation

https://github.com/lorenmt/reco

공식 코드

Bootstrapping Semantic Segmentation with Regional Contrast

https://github.com/louey233/toward-mutual-information

공식 코드

Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

https://github.com/louisdo2108/acs-nnu-net

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Efficient 3D Brain Tumor Segmentation with Axial-Coronal-Sagittal Embedding

https://github.com/love6tao/aoi-overfitting-team

공식 코드

The Second-place Solution for CVPR VISION 23 Challenge Track 1 -- Data Effificient Defect Detection

https://github.com/lsan2401/rmsin

공식 코드

Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation

https://github.com/lseventeen/dias

공식 코드

DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences

https://github.com/lseventeen/flare22-twostagephtrans

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Combining Self-Training and Hybrid Architecture for Semi-supervised Abdominal Organ Segmentation

https://github.com/lseventeen/phtrans

공식 코드

PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation

https://github.com/lslrh/cpsl

공식 코드

Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation

https://github.com/lslrh/dynamask

공식 코드

DynaMask: Dynamic Mask Selection for Instance Segmentation

https://github.com/lslrh/sim

공식 코드

SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation

https://github.com/lsmcolab/semantic-segmentation-under-adverse-conditions

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Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach

https://github.com/lstrgar/self-supervised-phone-segmentation

공식 코드

Phoneme Segmentation Using Self-Supervised Speech Models

https://github.com/lswzjuer/NAS-WDAN

공식 코드

MixSearch: Searching for Domain Generalized Medical Image Segmentation Architectures

https://github.com/lszcoding/clipsam

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ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation

https://github.com/ltcontext/ltcontext

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How Much Temporal Long-Term Context is Needed for Action Segmentation?

https://github.com/lttm/cl-pcss

공식 코드

Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data

https://github.com/lu-wo/detrtime

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A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications

https://github.com/lucasfidon/feta-inference

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Partial supervision for the FeTA challenge 2021

https://github.com/lucaswithai/visgraph

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End-to-end video instance segmentation via spatial-temporal graph neural networks

https://github.com/lucasxteixeira/covid19-segmentation-paper

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Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images

https://github.com/luckybird1994/ASAM

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ASAM: Boosting Segment Anything Model with Adversarial Tuning

https://github.com/luckybird1994/ipseg

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Towards Training-free Open-world Segmentation via Image Prompt Foundation Models

https://github.com/luckybird1994/samcod

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Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection

https://github.com/lufanma/ifr

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Implicit Feature Refinement for Instance Segmentation

https://github.com/luigifreda/plvs

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PLVS: A SLAM System with Points, Lines, Volumetric Mapping, and 3D Incremental Segmentation

https://github.com/luigiriz/nops

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Novel Class Discovery for 3D Point Cloud Semantic Segmentation

https://github.com/luizbuschetto/feulgen_nuclei_segmentation

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Towards a Complete Pipeline for Segmenting Nuclei in Feulgen-Stained Images

https://github.com/lukemelas/deep-spectral-segmentation

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Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization

https://github.com/lunn88/tak-semi

공식 코드

Leveraging Textual Anatomical Knowledge for Class-Imbalanced Semi-Supervised Multi-Organ Segmentation

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