arXiv:2104.14749
공식 코드 · Papers with Code
Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation
원문 초록
The following paper is a reproducibility report for "FDA: Fourier Domain Adaptation for Semantic Segmentation" published in the CVPR 2020 as part of the ML Reproducibility Challenge 2020. The original code was made available by the author. The well-commented version of the code containing all ablation studies performed derived from the original code along with WANDB integration is available at <github.com/thefatbandit/FDA> with proper instructions to execute experiments in README.
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A Novel Unsupervised Domain Adaption Method for Depth-Guided Semantic Segmentation Using Coarse-to-Fine Alignment
Pixel-level Intra-domain Adaptation for Semantic Segmentation
PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images
Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
Unlocking Constraints: Source-Free Occlusion-Aware Seamless Segmentation
SRPL-SFDA: SAM-Guided Reliable Pseudo-Labels for Source-Free Domain Adaptation in Medical Image Segmentation
토론
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