https://github.com/zhimin-c/bridge3d
공식 코드Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
Papers with Code 아카이브
Image Segmentation
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Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zhongaobo/asymmetry-bts
공식 코드https://github.com/zhongxuanwang/adv_attk
공식 코드Susceptibility of Adversarial Attack on Medical Image Segmentation Models
https://github.com/zhouweilian1904/HSI_Segmentation
공식 코드When Segmentation Meets Hyperspectral Image: New Paradigm for Hyperspectral Image Classification
https://github.com/zhu-xlab/aio2
공식 코드https://github.com/zhuhui100/fasunet
공식 코드FAS-UNet: A Novel FAS-driven Unet to Learn Variational Image Segmentation
https://github.com/zhuye98/icl
공식 코드Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation
https://github.com/zinic95/HFTrans
공식 코드https://github.com/ziqipang/addp
공식 코드https://github.com/zishuowan/voila
공식 코드VOILA: Complexity-Aware Universal Segmentation of CT images by Voxel Interacting with Language
https://github.com/zitongzhan/mmtracking/tree/zitongzhan/rovis/configs/vis/rovis
공식 코드Robust Online Video Instance Segmentation with Track Queries
https://github.com/ziyangwang007/cv-ssl-mis
공식 코드https://github.com/ziyangwang007/mamba-unet
공식 코드Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation
https://github.com/zjlab-ammi/q-net
공식 코드https://github.com/zju-vipa/BKT
공식 코드Visual Boundary Knowledge Translation for Foreground Segmentation
https://github.com/zjugivelab/scaleformer
공식 코드https://github.com/zmhhmz/resfu
공식 코드A Refreshed Similarity-based Upsampler for Direct High-Ratio Feature Upsampling
https://github.com/zongyi-lee/fusionu-net
공식 코드FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation
https://github.com/zongzi13545329/simada
공식 코드SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes
https://github.com/zwwwayne/k-net
공식 코드https://github.com/zx33/apaunet
공식 코드APAUNet: Axis Projection Attention UNet for Small Target in 3D Medical Segmentation
https://github.com/zyc00/point-sam
공식 코드Point-SAM: Promptable 3D Segmentation Model for Point Clouds
https://github.com/zymissy/ccvim
공식 코드Merging Context Clustering with Visual State Space Models for Medical Image Segmentation
https://github.com/zyun-y/dconnnet
공식 코드Directional Connectivity-based Segmentation of Medical Images
https://github.com/zzzqzhou/dual-normalization
공식 코드https://github.com/zzzqzhou/ram-dsir
공식 코드https://gitlab.com/4ndr3aR/pothole-mix-segmentation
공식 코드SHREC 2022: pothole and crack detection in the road pavement using images and RGB-D data
https://gitlab.com/NERSC/roofline-on-nvidia-gpus
공식 코드Hierarchical Roofline Performance Analysis for Deep Learning Applications
https://gitlab.com/emil-benedykciuk/u-net-darts-tensorflow
공식 코드https://gitlab.com/hararticles/orthovar
공식 코드https://github.com/04RR/SOTA-Vision
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
https://github.com/0bserver07/Keras-SegNet-Basic
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/0bserver07/One-Hundred-Layers-Tiramisu
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
https://github.com/0jason000/MobileNet_V2
https://github.com/0jason000/MobilleNetV3
https://github.com/0xzayd/Wnet-cGAN
U-Net: Convolutional Networks for Biomedical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.