https://github.com/xiaozhen228/caps
공식 코드Investigating Shift Equivalence of Convolutional Neural Networks in Industrial Defect Segmentation
Papers with Code 아카이브
Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xiarho/cmda
공식 코드CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation
https://github.com/xiechenxi99/mass13k
공식 코드https://github.com/xieenze/PolarMask
공식 코드PolarMask: Single Shot Instance Segmentation with Polar Representation
https://github.com/xieenze/Segment_Transparent_Objects
공식 코드https://github.com/xieenze/Trans2Seg
공식 코드https://github.com/xiizhao/cbn.pytorch
공식 코드CBNet: A Plug-and-Play Network for Segmentation-Based Scene Text Detection
https://github.com/xincheng-yang/pointcat
공식 코드https://github.com/xing0047/rewrite
공식 코드Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation
https://github.com/xing0047/tps
공식 코드Domain Adaptive Video Segmentation via Temporal Pseudo Supervision
https://github.com/xinge008/Cylinder3D
공식 코드Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
https://github.com/xingli1102/BEDs
공식 코드https://github.com/xingqunqi-lab/gkd-framework
공식 코드Exploring Generalizable Distillation for Efficient Medical Image Segmentation
https://github.com/xingy038/laser
공식 코드Laser: Efficient Language-Guided Segmentation in Neural Radiance Fields
https://github.com/xingzhehe/ganseg
공식 코드GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
https://github.com/xinyu-laura/mmuda
공식 코드https://github.com/xinzhel/word_corruption
공식 코드Can Pretrained Language Models Derive Correct Semantics from Corrupt Subwords under Noise?
https://github.com/xishufan/crosstooth_cvpr2025
공식 코드3D Dental Model Segmentation with Geometrical Boundary Preserving
https://github.com/xiweix/reme
공식 코드ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation
https://github.com/xjwu1024/WPS-SAM
공식 코드WPS-SAM: Towards Weakly-Supervised Part Segmentation with Foundation Models
https://github.com/xlhex/dpe
공식 코드Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation
https://github.com/xmed-lab/GraphEcho
공식 코드GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
https://github.com/xmed-lab/clip_surgery
공식 코드A Closer Look at the Explainability of Contrastive Language-Image Pre-training
https://github.com/xmed-lab/css-semivideo
공식 코드https://github.com/xmed-lab/mssg
공식 코드Morphology-inspired Unsupervised Gland Segmentation via Selective Semantic Grouping
https://github.com/xmed-lab/oeem
공식 코드Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images
https://github.com/xmed-lab/urn
공식 코드https://github.com/xmeimeimei/sgtc
공식 코드https://github.com/xmengli999/Deeply-Supervised-Rotation-Equivariant-Network-for-Lesion-Segmentation
공식 코드Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images
https://github.com/xmindflow/braincl
공식 코드Modality-Independent Brain Lesion Segmentation with Privacy-aware Continual Learning
https://github.com/xmindflow/cenet
공식 코드CENet: Context Enhancement Network for Medical Image Segmentation
https://github.com/xmindflow/fusenet
공식 코드FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation
https://github.com/xmindflow/lhunet
공식 코드https://github.com/xmindflow/met-seg
공식 코드https://github.com/xmindflow/msa-2net
공식 코드MSA$^2$Net: Multi-scale Adaptive Attention-guided Network for Medical Image Segmentation
https://github.com/xmlyqing00/AFB-URR
공식 코드Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.