https://github.com/yuhangzang/FASA
공식 코드FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation
Papers with Code 아카이브
Semantic Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yuhangzang/contextdet
공식 코드Contextual Object Detection with Multimodal Large Language Models
https://github.com/yuhoo0302/segment-anything-model-for-medical-images
공식 코드https://github.com/yuhuan-wu/P2T
공식 코드https://github.com/yuhuan-wu/RDPNet
공식 코드Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
https://github.com/yuhuan-wu/lrformer
공식 코드https://github.com/yuhui-zh15/transseg
공식 코드https://github.com/yujun0-0/mma-net
공식 코드VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
https://github.com/yuk6heo/GIS-RAmap
공식 코드Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps
https://github.com/yuk6heo/IVOS-ATNet
공식 코드Interactive Video Object Segmentation Using Global and Local Transfer Modules
https://github.com/yukang2017/RENAS
공식 코드https://github.com/yukang2017/Stitcher
공식 코드https://github.com/yukekejan/uccl
공식 코드Uncertainty-Participation Context Consistency Learning for Semi-supervised Semantic Segmentation
https://github.com/yuki-11/csbsr
공식 코드Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images
https://github.com/yulequan/UA-MT
공식 코드Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation
https://github.com/yuliangguo/Pytorch_Generalized_3D_Lane_Detection
공식 코드Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection
https://github.com/yummy198913/iv-tuning
공식 코드IV-tuning: Parameter-Efficient Transfer Learning for Infrared-Visible Tasks
https://github.com/yun-liu/MiniSeg
공식 코드MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
https://github.com/yun-liu/hat-net
공식 코드https://github.com/yunfan1202/Delving-into-Crispness
공식 코드Delving into Crispness: Guided Label Refinement for Crisp Edge Detection
https://github.com/yunkezhang/TCVOM
공식 코드https://github.com/yunlong10/CAT-V
공식 코드https://github.com/yunongLiu1/IKEA-Manuals-at-Work
공식 코드IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
https://github.com/yunshin/SphericalMask
공식 코드Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation
https://github.com/yunwilliamyu/severability
공식 코드Severability of mesoscale components and local time scales in dynamical networks
https://github.com/yunxiangfu2001/segman
공식 코드https://github.com/yunyagaotree/sam-adapter-for-refugee-dwelling-extraction
공식 코드https://github.com/yupeiyu98/deep-region-competition
공식 코드Unsupervised Foreground Extraction via Deep Region Competition
https://github.com/yupeiyu98/drc
공식 코드Unsupervised Foreground Extraction via Deep Region Competition
https://github.com/yurongchen1998/yurong-lib
공식 코드Towards to Robust and Generalized Medical Image Segmentation Framework
https://github.com/yutao1008/mswin
공식 코드Self-attention on Multi-Shifted Windows for Scene Segmentation
https://github.com/yuweihao/mambaout
공식 코드https://github.com/yuwenlo/hardnet-dfus
공식 코드https://github.com/yuxiaodonghri/soit
공식 코드https://github.com/yuyangsheng/surgical-desam
공식 코드Surgical-DeSAM: Decoupling SAM for Instrument Segmentation in Robotic Surgery
https://github.com/yuyijiong/remote_sense_image_quality_inspection
공식 코드An Intelligent Remote Sensing Image Quality Inspection System
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.