Cover Image

FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Xiaoyang, Wu, Xiaoming, Wang, Xin, Li, Dongrun, Yang, Ming, Cheng, Peng
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Choice Outweighs Effort: Facilitating Complementary Knowledge Fusion in Federated Learning via Re-calibration and Merit-discrimination
by: Yang, Ming, et al.
Published: (2025)

FedeCouple: Fine-Grained Balancing of Global-Generalization and Local-Adaptability in Federated Learning
by: Yang, Ming, et al.
Published: (2025)

FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer
by: Gao, Xin, et al.
Published: (2024)

Adaptive Prototype Replay for Class Incremental Semantic Segmentation
by: Zhu, Guilin, et al.
Published: (2024)

FedNSAM:Consistency of Local and Global Flatness for Federated Learning
by: Liu, Junkang, et al.
Published: (2026)

FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning
by: Zhou, Yanbing, et al.
Published: (2025)

Task Consistent Prototype Learning for Incremental Few-shot Semantic Segmentation
by: Xu, Wenbo, et al.
Published: (2024)

FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness
by: Xiang, Yangyang, et al.
Published: (2024)

Domain-invariant Prototypes for Semantic Segmentation
by: Yang, Zhengeng, et al.
Published: (2022)

FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
by: Peng, Hongyi, et al.
Published: (2024)

FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
by: Zhang, Yong, et al.
Published: (2025)

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning
by: Kou, Zhiqiang, et al.
Published: (2026)

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching
by: Wang, Huan, et al.
Published: (2026)

FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation
by: Yang, Yingguang, et al.
Published: (2026)

FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning
by: Tang, Minxue, et al.
Published: (2024)

FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes
by: Guo, Fucheng, et al.
Published: (2025)

Prototype Contrastive Consistency Learning for Semi-Supervised Medical Image Segmentation
by: He, Shihuan, et al.
Published: (2025)

Revisiting Efficient Semantic Segmentation: Learning Offsets for Better Spatial and Class Feature Alignment
by: Zhang, Shi-Chen, et al.
Published: (2025)

Leveraging Swin Transformer for Local-to-Global Weakly Supervised Semantic Segmentation
by: Ahmadi, Rozhan, et al.
Published: (2024)

SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation
by: Zhao, Xinqiao, et al.
Published: (2024)

FedRFQ: Prototype-Based Federated Learning with Reduced Redundancy, Minimal Failure, and Enhanced Quality
by: Yan, Biwei, et al.
Published: (2024)

FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning
by: Zhang, Jianqing, et al.
Published: (2024)

Context Patch Fusion With Class Token Enhancement for Weakly Supervised Semantic Segmentation
by: Fu, Yiyang, et al.
Published: (2026)

HarmoniAD: Harmonizing Local Structures and Global Semantics for Anomaly Detection
by: Zhang, Naiqi, et al.
Published: (2026)

FedDBP: Enhancing Federated Prototype Learning with Dual-Branch Features and Personalized Global Fusion
by: Gao, Ningzhi, et al.
Published: (2026)

Subspace Prototype Guidance for Mitigating Class Imbalance in Point Cloud Semantic Segmentation
by: Han, Jiawei, et al.
Published: (2024)

P-SLCR: Unsupervised Point Cloud Semantic Segmentation via Prototypes Structure Learning and Consistent Reasoning
by: Zhan, Lixin, et al.
Published: (2026)

FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
by: Tan, Min, et al.
Published: (2026)

Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic Segmentation
by: Tang, Feilong, et al.
Published: (2024)

FedDSR: Federated Deep Supervision and Regularization Towards Autonomous Driving
by: Kou, Wei-Bin, et al.
Published: (2025)

FedBAP: Backdoor Defense via Benign Adversarial Perturbation in Federated Learning
by: Yan, Xinhai, et al.
Published: (2025)

DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
by: Qi, Mengshi, et al.
Published: (2025)

Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation
by: Kim, David Minkwan, et al.
Published: (2025)

FedGCA: Global Consistent Augmentation Based Single-Source Federated Domain Generalization
by: Liu, Yuan, et al.
Published: (2024)

Static-Dynamic Class-level Perception Consistency in Video Semantic Segmentation
by: Cen, Zhigang, et al.
Published: (2024)

SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for Medical Image Segmentation
by: Nasirihaghighi, Sahar, et al.
Published: (2025)

Class Incremental Medical Image Segmentation via Prototype-Guided Calibration and Dual-Aligned Distillation
by: Zhu, Shengqian, et al.
Published: (2025)

SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering
by: Ren, Qingnan, et al.
Published: (2026)

MoRe: Class Patch Attention Needs Regularization for Weakly Supervised Semantic Segmentation
by: Yang, Zhiwei, et al.
Published: (2024)

Mitigating Spurious Correlations in Weakly Supervised Semantic Segmentation via Cross-architecture Consistency Regularization
by: Zhang, Zheyuan, et al.
Published: (2025)