State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal sequence modeling. While effective for sequential data, directional scanning introduces spatial bias and orientation-sensitive representations. We present Vision Non-Causal Trapezoidal Mamba (VNCT), a second-order non-causal vision SSM that enables all image tokens to interact in a single pass, eliminating direSctional scanning and achieving low single-image inference latency. VNCT exhibits more orientation-robust representations, showing reduced performance degradation under image rotations and flips, while improving Boundary IoU by up to 3.7 points, leading to more accurate boundary preservation and object localization. Across ImageNet-1K classification, COCO object detection and instance segmentation, and ADE20K semantic segmentation, VNCT consistently outperforms both directional-scanning vision SSMs and first-order non-causal SSMs. These results show that directional scanning is unnecessary for high-performance vision SSMs and that second-order non-causal state-space modeling offers a simple, efficient, and robust alternative for visual recognition.
Mamba, a State Space Model (SSM), has recently shown competitive performance to Convolutional Neural Networks (CNNs) and Transformers in Natural Language Processing and general sequence modeling. Various attempts have been made to adapt Mamba to Computer Vision tasks, including medical image segmentation (MIS). Vision Mamba (VM)-based networks are particularly attractive due to their ability to achieve global receptive fields, similar to Vision Transformers, while also maintaining linear complexity in the number of tokens. However, the existing VM models still struggle to maintain both spatial…
ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation
Wuhan University of Technology（武汉理工大学）；Chinese Academy of Medical Sciences and Peking Union Medical College（中国医学科学院北京协和医学院）；Zhongnan Hospital of Wuhan University（武汉大学中南医院）
DA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection
Intelligent Software Research Center, Institute of Software, CAS（软件研究所智能软件研究中心，中国科学院）；State Key Lab of Processors, Institute of Computing Technology, CAS（中国科学院计算技术研究所处理器国家重点实验室）；School of Information Science and Technology, University of Science and Technology of China（中国科学技术大学信息科学与技术学校）
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
School of EIC, Huazhong University of Science & Technology（华中科技大学电子信息与通信学院）；Institute of Artificial Intelligence, Huazhong University of Science & Technology（华中科技大学人工智能研究院）；Horizon Robotics（地平线机器人）；Beijing Academy of Artificial Intelligence（北京智源人工智能研究院）
U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation
Peter Munk Cardiac Centre, University Health Network（彼得·蒙克心脏中心，大学健康网络）；University of Toronto（多伦多大学）；Vector Institute for Artificial Intelligence（向量人工智能研究所）
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection
The Hong Kong Polytechnic University（香港理工大学）；Center for Artificial Intelligence and Robotics, HKISI, CAS（中国科学院香港智能科学研究所人工智能与机器人中心）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation
School of Computer Science, Peking University（北京大学计算机学院）；Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能研究院）；Key Laboratory of High Confidence Software Technologies, Ministry of Education（教育部高可信软件技术重点实验室）；National Engineering Research Center for Software Engineering, Peking University（北京大学国家软件工程研究中心）
VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation
State Key Laboratory for Novel Software Technology, Nanjing University（南京大学计算机软件新技术国家重点实验室）；Huazhong University of Science and Technology（华中科技大学）；Jiangsu Province Hospital of Chinese Medicine（江苏省中医院）
D2-Mamba: Dual-Scale Fusion and Dual-Path Scanning with SSMs for Shadow Removal
School of Artificial Intelligence, Hebei University of Technology（人工智能学院，河北工业大学）；School of Electrical and Computer Engineering, University of Texas at Austin（电气与计算机工程学院，德克萨斯大学奥斯汀分校）；School of Health Sciences and Biomedical Engineering, Hebei University of Technology（健康科学与生物医学工程学院，河北工业大学）
Trajectory-aware Shifted State Space Models for Online Video Super-Resolution
Pengcheng Labartory（鹏城实验室）；University of Bristol（英国布里斯托大学）；University of Electronic Science and Technology of China（电子科技大学）；Shenzhen Graduate School, Peking University（北京大学深圳研究生院）
Motion Mamba: Efficient and Long Sequence Motion Generation
Monash University（莫纳什大学）；The Australian National University（澳大利亚国立大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Peking University（北京大学）
Vivim: a Video Vision Mamba for Medical Video Segmentation
The Hong Kong University of Science and Technology, Guangzhou（香港科技大学（广州））；The University of Hong Kong（香港大学）；Guangdong Provincial People’s Hospital（广东省人民医院）；Institute of High Performance Computing, A*STAR（新加坡高性能计算研究院（新加坡科研局下属机构））；Hong Kong University of Science and Technology（香港科技大学）
Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model
Department of Electrical and Computer Engineering, Sungkyunkwan University（电气与计算机工程系，全北大学）；Department of Artificial Intelligence, Sungkyunkwan University（人工智能系，全北大学）；Hanwha Systems, Republic of Korea（韩华系统，韩国）；Department of Artificial Intelligence, Yonsei University（人工智能系，延世大学）
AS-Mamba: Asymmetric Self-Guided Mamba Decoupled Iterative Network for Metal Artifact Reduction
School of Information Engineering, Nanchang University（信息工程学院，南昌大学）；School of Mathematics and Computer Sciences, Nanchang University（数学与计算机科学学院，南昌大学）；The First Affiliated Hospital, Jiangxi Medical College, Nanchang University（江西医学院第一附属医院，南昌大学）；LargeV Instrument Corp., Ltd.（大维仪器有限公司）
Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis
School of Biomedical Engineering（生物医学工程学院）；University of British Columbia（不列颠哥伦比亚大学）；Tarbiat Modares University（塔比亚特·莫达雷斯大学）；University of Regensburg（雷根斯堡大学）；South Dakota State University（南达科他州立大学）；RWTH Aachen University（亚琛工业大学）；Lunit Inc.（Lunit公司）；Northwestern University（西北大学）；Fraunhofer Institute for Digital Medicine（弗劳恩霍夫数字医学研究院）
