Copertina

SP-Mamba: Spatial-Perception State Space Model for Unsupervised Medical Anomaly Detection

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pan, Rui, Lu, Ruiying
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
di: He, Haoyang, et al.
Pubblicazione: (2024)

CollaMamba: Efficient Collaborative Perception with Cross-Agent Spatial-Temporal State Space Model
di: Li, Yang, et al.
Pubblicazione: (2024)

Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection
di: Iqbal, Nasar, et al.
Pubblicazione: (2025)

SpectMamba: Integrating Frequency and State Space Models for Enhanced Medical Image Detection
di: Wang, Yao, et al.
Pubblicazione: (2025)

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection
di: Erdil, Ertunc, et al.
Pubblicazione: (2026)

SP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution
di: Zou, Wenbin, et al.
Pubblicazione: (2026)

CoMamba: Real-time Cooperative Perception Unlocked with State Space Models
di: Li, Jinlong, et al.
Pubblicazione: (2024)

PAS-Mamba: Phase-Amplitude-Spatial State Space Model for MRI Reconstruction
di: Kui, Xiaoyan, et al.
Pubblicazione: (2026)

CloudMamba: Grouped Selective State Spaces for Point Cloud Analysis
di: Qu, Kanglin, et al.
Pubblicazione: (2025)

CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration
di: Deng, Rui, et al.
Pubblicazione: (2024)

Spatial-Mamba: Effective Visual State Space Models via Structure-aware State Fusion
di: Xiao, Chaodong, et al.
Pubblicazione: (2024)

SR-Mamba: Effective Surgical Phase Recognition with State Space Model
di: Cao, Rui, et al.
Pubblicazione: (2024)

STNMamba: Mamba-based Spatial-Temporal Normality Learning for Video Anomaly Detection
di: Li, Zhangxun, et al.
Pubblicazione: (2024)

DefMamba: Deformable Visual State Space Model
di: Liu, Leiye, et al.
Pubblicazione: (2025)

Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
di: Li, Chunlei, et al.
Pubblicazione: (2025)

Pan-Mamba: Effective pan-sharpening with State Space Model
di: He, Xuanhua, et al.
Pubblicazione: (2024)

MFil-Mamba: Multi-Filter Scanning for Spatial Redundancy-Aware Visual State Space Models
di: Khadka, Puskal, et al.
Pubblicazione: (2026)

MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation
di: Tang, Fenghe, et al.
Pubblicazione: (2024)

Mamba YOLO: A Simple Baseline for Object Detection with State Space Model
di: Wang, Zeyu, et al.
Pubblicazione: (2024)

HTD-Mamba: Efficient Hyperspectral Target Detection with Pyramid State Space Model
di: Shen, Dunbin, et al.
Pubblicazione: (2024)

Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning
di: Cheng, De, et al.
Pubblicazione: (2024)

HydraMamba: Multi-Head State Space Model for Global Point Cloud Learning
di: Qu, Kanglin, et al.
Pubblicazione: (2025)

MambaDETR: Query-based Temporal Modeling using State Space Model for Multi-View 3D Object Detection
di: Ning, Tong, et al.
Pubblicazione: (2024)

Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection
di: Liu, Xinyue, et al.
Pubblicazione: (2024)

MambaMoE: Mixture-of-Spectral-Spatial-Experts State Space Model for Hyperspectral Image Classification
di: Xu, Yichu, et al.
Pubblicazione: (2025)

ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Model
di: Wang, Guanchun, et al.
Pubblicazione: (2025)

DA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection
di: Li, Haochen, et al.
Pubblicazione: (2026)

ChessMamba: Structure-Aware Interleaving of State Spaces for Change Detection in Remote Sensing Images
di: Ding, Lei, et al.
Pubblicazione: (2025)

VADMamba: Exploring State Space Models for Fast Video Anomaly Detection
di: Lyu, Jiahao, et al.
Pubblicazione: (2025)

MambaTAD: When State-Space Models Meet Long-Range Temporal Action Detection
di: Lu, Hui, et al.
Pubblicazione: (2025)

URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
di: Luo, Wei, et al.
Pubblicazione: (2026)

SpectralMamba-UNet: Frequency-Disentangled State Space Modeling for Texture-Structure Consistent Medical Image Segmentation
di: Zhang, Fuhao, et al.
Pubblicazione: (2026)

Point Cloud Mamba: Point Cloud Learning via State Space Model
di: Zhang, Tao, et al.
Pubblicazione: (2024)

Vision-Language Models Assisted Unsupervised Video Anomaly Detection
di: Jiang, Yalong, et al.
Pubblicazione: (2024)

Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces
di: Feng, Yaoxuan, et al.
Pubblicazione: (2026)

M2S2L: Mamba-based Multi-Scale Spatial-temporal Learning for Video Anomaly Detection
di: Liu, Yang, et al.
Pubblicazione: (2025)

DensePercept-NCSSD: Vision Mamba towards Real-time Dense Visual Perception with Non-Causal State Space Duality
di: Anand, Tushar, et al.
Pubblicazione: (2025)

S$^2$Mamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification
di: Wang, Guanchun, et al.
Pubblicazione: (2024)

Mamba-Adaptor: State Space Model Adaptor for Visual Recognition
di: Xie, Fei, et al.
Pubblicazione: (2025)

U-Shape Mamba: State Space Model for faster diffusion
di: Ergasti, Alex, et al.
Pubblicazione: (2025)