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/ruipingl/skr_pea
공식 코드TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation
https://github.com/ruipingl/transkd
공식 코드TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation
https://github.com/ruiqixu37/BTTS_ECAI2023
공식 코드Specializing Small Language Models towards Complex Style Transfer via Latent Attribute Pre-Training
https://github.com/ruirangerfan/road_crack_detection_net
공식 코드Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding
https://github.com/ruizhe-l/semi-segmentation
공식 코드https://github.com/runminjiang/pw4medseg
공식 코드Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning
https://github.com/runnanchen/clip2scene
공식 코드CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
https://github.com/runnanchen/label-free-scene-understanding
공식 코드Towards Label-free Scene Understanding by Vision Foundation Models
https://github.com/ruochengao/swin_litemedsam
공식 코드https://github.com/rusu4943/3d-sfuda
공식 코드Cross-Domain Distribution Alignment for Segmentation of Private Unannotated 3D Medical Images
https://github.com/rwightman/pytorch-image-models
공식 코드How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
https://github.com/ryersonmultimedialab/dynaseg
공식 코드https://github.com/ryh1218/occ
공식 코드Prohibited Items Segmentation via Occlusion-aware Bilayer Modeling
https://github.com/s-nlp/lewit-informal
공식 코드Don't lose the message while paraphrasing: A study on content preserving style transfer
https://github.com/s-sd/spurl
공식 코드Competing for pixels: a self-play algorithm for weakly-supervised segmentation
https://github.com/saadwazir/HistoSeg
공식 코드https://github.com/saadwazir/ReN-UNet
공식 코드https://github.com/saadwazir/mcads-decoder
공식 코드https://github.com/sabarim/3DC-Seg
공식 코드Making a Case for 3D Convolutions for Object Segmentation in Videos
https://github.com/sadjadrz/Lung-segmentation-dataset
공식 코드FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
https://github.com/sadjadrz/fusionlungnet
공식 코드FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
https://github.com/safouaneelg/FusionVision
공식 코드https://github.com/sagieppel/Generator-evaluator-selector-net-a-modular-approach-for-panoptic-segmentation
공식 코드https://github.com/sagieppel/LabPics-medical-Computer-vision-for-liquid-samples-in-hospitals-and-medical-lab-
공식 코드https://github.com/sagieppel/Pointer-based-segmentation-find-segment-containing-given-image-point-witin-given-ROI-mask-using-CNN
공식 코드https://github.com/sagieppel/Splitting-unfamiliar-objects-and-stuff-in-images-into-parts-using-neural-nets
공식 코드https://github.com/saitpublic/doctr
공식 코드DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding
https://github.com/sakaridis/MGCDA
공식 코드https://github.com/sakibsourav019/streetlight_control_multiclass_segmentation_-camvid-_unet_keras
공식 코드CNN based Intelligent Streetlight Management Using Smart CCTV Camera and Semantic Segmentation
https://github.com/sakurajimamaiii/protokd
공식 코드Prototype Knowledge Distillation for Medical Segmentation with Missing Modality
https://github.com/sakurajimamaiii/tsd
공식 코드https://github.com/sallymmx/TransVOS
공식 코드https://github.com/salmanmaq/segmentationNetworks
공식 코드m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks
https://github.com/sam1224/fssam
공식 코드https://github.com/sampolk/d-vic
공식 코드Active Diffusion and VCA-Assisted Image Segmentation of Hyperspectral Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.