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Semantic Segmentation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DirtyHarryLYL/SRDA-ECCV2018
공식 코드SRDA: Generating Instance Segmentation Annotation Via Scanning, Reasoning And Domain Adaptation
https://github.com/DmitriiShubin/Variance-Aware-Training
공식 코드https://github.com/Dmmm1997/DeRIS
공식 코드https://github.com/DoctorKey/C-3PO
공식 코드https://github.com/DrSleep/multi-task-refinenet
공식 코드Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
https://github.com/Duankaiwen/LSNet
공식 코드https://github.com/DylanWusee/pointconv
공식 코드https://github.com/EKirschbaum/DISCo
공식 코드https://github.com/EMI-Group/FaPN
공식 코드FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
https://github.com/EMI-Group/RelativeNAS
공식 코드RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning
https://github.com/ENSTA-U2IS-AI/Multimodal_Deep_segmentation
공식 코드InfraParis: A multi-modal and multi-task autonomous driving dataset
https://github.com/ENSTA-U2IS-AI/torch-uncertainty
공식 코드https://github.com/EPFL-VILAB/MultiMAE
공식 코드https://github.com/ESA-PhiLab/CAS_Confidence_Assessment
공식 코드Improving EO Foundation Models with Confidence Assessment for enhanced Semantic segmentation
https://github.com/ESA-PhiLab/PhilEO-Bench
공식 코드https://github.com/ESA-PhiLab/PhilEO-MajorTOM
공식 코드Scaling-Up the Pretraining of the Earth Observation Foundation Model PhilEO to the MajorTOM Dataset
https://github.com/ESandML/FCBFormer
공식 코드https://github.com/ETHRuiGong/DLOW
공식 코드https://github.com/ETHRuiGong/TADA
공식 코드https://github.com/EagleMIT/EMKD
공식 코드Efficient Medical Image Segmentation Based on Knowledge Distillation
https://github.com/Edge-AI-Acceleration-Lab/RBFleX-NAS
공식 코드https://github.com/Ekim-Yurtsever/DeepTL-Lane-Change-Classification
공식 코드https://github.com/EliasKassapis/CARMSS
공식 코드Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
https://github.com/EliasKassapis/CARSSS
공식 코드Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
https://github.com/EmbodiedVision/slot_attention_normalization
공식 코드Attention Normalization Impacts Cardinality Generalization in Slot Attention
https://github.com/EmmaW8/BEAL
공식 코드Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation
https://github.com/Engineering-Course/LIP_SSL
공식 코드Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
https://github.com/Epiphqny/VisTR
공식 코드https://github.com/EricFH/salient_object_ranking_with_PPA
공식 코드https://github.com/ErikStammes/EADER
공식 코드Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation
https://github.com/Erosinho13/FedDrive
공식 코드FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving
https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-DINO
공식 코드Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-DPT
공식 코드Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-Segmenter
공식 코드Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
https://github.com/ExplainableML/cosmos
공식 코드COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.