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/WangPing521/self-paced-and--self-consistent-semi-supervised-segmentation
Self-paced and self-consistent co-training for semi-supervised image segmentation
https://github.com/WangWenhao0716/DomainMix
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/Wangyixinxin/MMedAgent
https://github.com/WarBean/tps_stn_pytorch
https://github.com/WenmuZhou/PytorchOCR
https://github.com/WenmuZhou/Segmentation-Free_OCR
https://github.com/WenmuZhou/crnn.pytorch
https://github.com/Whiffe/mmaction2_YF
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/WhiskyChoy/language-style-transfer
https://github.com/Will-J-Gale/Self-Driving-Car-Vision
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/WonJunPark/swinUNet_custom_training
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
https://github.com/Wordbe/MobileNetV2
https://github.com/WuJunde/DiagnosisFirst
Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle
https://github.com/X-rayLaser/multi-directional-mdrnn
https://github.com/XXXVincent/MonoDepth2
https://github.com/XavierJiezou/D2LS
Dynamic Dictionary Learning for Remote Sensing Image Segmentation
https://github.com/XavierJiezou/KTDA
Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation
https://github.com/XiangbingJi/Stanford-cs230-final-project
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/Xiaoqi-Zhao-DLUT/GateNet-RGB-Saliency
https://github.com/XiongweiWu/FoodSeg103-Benchmark-v1
https://github.com/Yang-Q-D/mindsporeCode/tree/master/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/Yangzhangcst/AF-graph_all
Affinity Fusion Graph-based Framework for Natural Image Segmentation
https://github.com/YanjieZe/Virtual-Multi-View-Fusion
https://github.com/Yashgh7076/CU-Thesis
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/YeLyuUT/UAVidToolKit
https://github.com/YeLyuUT/semantic_segmentation
Bidirectional Multi-scale Attention Networks for Semantic Segmentation of Oblique UAV Imagery
https://github.com/YellowLight021/Vnet
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
https://github.com/YeongHyeon/Skip-GANomaly
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection
https://github.com/Yijunmaverick/GenerativeFaceCompletion
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/Yimin-Yuan/VeinProject
https://github.com/YininKorea/Contour-aware-equipotential-learning
https://github.com/YoungXIAO13/FewShotDetection
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild
https://github.com/YoungXIAO13/PoseContrast
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild
https://github.com/YourGc/Unet_jinnan2
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/YuanXue1993/SegAN
SegAN: Adversarial Network with Multi-scale $L_1$ Loss for Medical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.