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Code for Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach
The main features of lianqing11/pycda are: Semantic Segmentation.
Projects with overlapping indexed features include: bit-da/sepico — [TPAMI 2023 ESI Highly Cited Paper] SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation… brdav/refign — Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions [WACV 2023]. bupt-ai-cz/cac-unet-digestpath2019 — 1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue… bupt-ai-cz/iast-eccv2020 — IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)… charlesq34/frustum-pointnets — Created by Charles R. Qi , Wei Liu , Chenxia Wu , Hao Su and Leonidas J. Guibas from Stanford University and Nuro Inc. a514514772/dise-domain-invariant-structure-extraction — Pytorch Implementation -- All about Structure: Adapting Structural Information across Domains for Boosting Semantic…
TPAMI 2023 ESI Highly Cited Paper SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation https://arxiv.org/abs/2204.08808
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions WACV 2023
1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
Pytorch Implementation -- All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation, CVPR 2019