Papers with Code 아카이브
2D Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/yubaoliu/caffe-segnet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/yubaoliu/rds-slam
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/yueruchen/sppnet-pytorch
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
https://github.com/yuhsijen/Object-Detector
https://github.com/yuhuan-wu/EDN
https://github.com/yuhuan-wu/RDPNet
https://github.com/yuhuan-wu/mobilesal
https://github.com/yui-mhcp/base_dl_project
https://github.com/yuki3-18/Topological-DVAE
A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
https://github.com/yumaloop/kaggle-tgs-salt-competition
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/yumaloop/mobilenetV2-cifar
https://github.com/yunzeman/lexicon3d
Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Understanding
https://github.com/yuqizhu/covid19-classification
Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
https://github.com/yuranusduke/TransCNN
https://github.com/ywcmaike/TianchiVideoCharacterSegmentationPreliminary
https://github.com/yxgeee/MMT
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/yxgeee/SpCL
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/yxinjiang/Unet-for-foreground-segmentation
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation
https://github.com/z01nl1o02/deeplab-v2
https://github.com/zacharie12/zacharie
Learning to Compose Dynamic Tree Structures for Visual Contexts
https://github.com/zamnius/uNet-seg-decathlon
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/zampie/Animation-standing-segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/zampie/unet-colorization-pytorch
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/zarif101/blood_cell_segmentation_unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/zawlin/cvpr17_vtranse
Visual Translation Embedding Network for Visual Relation Detection
https://github.com/ze-yang/lgkd
https://github.com/zej-luffy/deeplab-public-ver2
https://github.com/zh320/medical-segmentation-pytorch
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/zh320/realtime-semantic-segmentation-pytorch
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/zhang-tao-whu/DVIS
DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries
https://github.com/zhangchi9/Airbus_Ship_Detection
https://github.com/zhangximing666/Auto-DeepLab_MS
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
https://github.com/zhangzjn/emo
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/zhangzjn/emov2
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/zhaominyiz/c3-stisr
Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.