Papers Long-range modeling
“Long-range modeling” 태그가 달린 논문 141편 · 필터 해제
CSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation
Accurate polyp segmentation is critical for computer-aided colonoscopy, yet endoscopic images often contain low-contrast boundaries, mucosal texture interference, specular highlights, and device-dependent appearance shif…
Long-range modelingPolyp SegmentationCLUIE: Clustering-Aware Recurrent Propagation with Local Structural Compensation for Underwater Image Enhancement
Underwater image enhancement remains challenging due to wavelength-dependent light absorption, scattering, and backscattering, which jointly cause color distortion, contrast degradation, and detail loss. Since these degr…
Long-range modelingImage EnhancementE-TraMamba: A New Paradigm for Efficient Long-Term 3D Feature Tracking with Event Cameras
Event-based 3D tracking enables low-latency and high-speed perception, while existing CNN- and Transformer-based trackers struggle to capture long-range spatiotemporal dependencies in sparse, noisy event streams, especia…
Long-range modelingVisual OdometryState Space Models Meet Remote Sensing: A Survey
State Space Models (SSMs), designed for long-range modeling, offer linear computational complexity and strong capabilities in capturing long-range dependencies. In the field of remote sensing, SSMs have gained popularity…
Long-range modelingProgressive Pixel-Neighborhood Deformable Cross-Attention for Multispectral Object Detection
Effective cross-modal feature alignment and interaction are central challenges in multispectral object detection. Although global cross-attention provides strong long-range modeling ability, its quadratic complexity with…
Multispectral Object DetectionSemantic correspondenceLong-range modelingReload-Mamba: Hierarchical Anti-Dilution State-Space Modeling for Multi-Class Semantic Segmentation
Mamba-based state space models offer linear-time long-range modeling for high-resolution dense prediction, but sequential state-space propagation can attenuate boundary-sensitive and detail-sensitive responses that are c…
Semantic SegmentationLong-range modelingDeepMine-Mamba: Mitigating Information Dilution in Mamba-Based State Space Models for Document Image Binarization
Document image binarization aims to separate foreground text from degraded backgrounds while preserving thin, broken, and low-contrast strokes. Although deep learning methods have improved binarization performance, most …
Long-range modelingSP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution
State space models (SSMs) have emerged as a powerful paradigm for efficient single-image super-resolution (SR) due to their linear complexity and long-range modeling capabilities. However, existing Mamba-based methods ty…
Image Super-ResolutionLong-range modelingSO-Mamba: State-Ownership Mamba for Unrolled MRI Reconstruction
Accelerated MRI reconstruction requires recovering missing details while preserving anatomically coherent structures across large spatial regions. State-space models such as Mamba provide efficient long-range modeling, m…
Computational EfficiencyLong-range modelingMRI ReconstructionCan Graphs Help Vision SSMs See Better?
Vision state space models inherit the efficiency and long-range modeling ability of Mamba-style selective scans. However, their performance depends critically on the representation of two-dimensional visual features as o…
Semantic SegmentationInstance SegmentationImage ClassificationLong-range modelingBreaking Spatial Uniformity: Prior-Guided Mamba with Radial Serialization for Lens Flare Removal
Lens flares, caused by complex optical aberrations, severely degrade image quality especially in nighttime photography. Although recent restoration methods have made remarkable progress, most still rely on spatially unif…
Long-range modelingFlare RemovalFLUID: Continuous-Time Hyperconnected Sparse Transformer for Sink-Free Learning
Continuous-time (CT) Transformers improve irregular and long-range modeling over CT-RNNs by exploiting inputs or outputs embeddings with continuous dynamics. However, the core scaled-dot-product-attention (SDPA) mechanis…
Long-range modelingAutonomous VehiclesSAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression
Perceptual image compression focuses on preserving high visual quality under low-bitrate constraints. Most existing approaches to perceptual compression leverage the strong generative capabilities of generative adversari…
Long-range modelingImage CompressionVision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models
Spiking Transformers have shown strong potential for long-range visual modeling through spike-driven self-attention. However, their quadratic token interactions remain fundamentally misaligned with the sparse and event-d…
Long-range modelingRayMamba: Ray-Aligned Serialization for Long-Range 3D Object Detection
Long-range 3D object detection remains challenging because LiDAR observations become highly sparse and fragmented in the far field, making reliable context modeling difficult for existing detectors. To address this issue…
Long-range modeling3D Object DetectionBridging the Geometry Mismatch: Frequency-Aware Anisotropic Serialization for Thin-Structure SSMs
The segmentation of thin linear structures is inherently topology allowbreak-critical, where minor local errors can sever long-range connectivity. While recent State-Space Models (SSMs) offer efficient long-range modelin…
Long-range modelingDA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection
Domain Adaptive Object Detection (DAOD) aims to transfer detectors from a labeled source domain to an unlabeled target domain. Existing DAOD methods employ multi-granularity feature alignment to learn domain-invariant re…
Long-range modelingObject DetectionInter-Image Pixel Shuffling for Multi-focus Image Fusion
Multi-focus image fusion aims to combine multiple partially focused images into a single all-in-focus image. Although deep learning has shown promise in this task, its effectiveness is often limited by the scarcity of su…
Long-range modelingRank-Factorized Implicit Neural Bias: Scaling Super-Resolution Transformer with FlashAttention
Recent Super-Resolution~(SR) methods mainly adopt Transformers for their strong long-range modeling capability and exceptional representational capacity. However, most SR Transformers rely heavily on relative positional …
Long-range modelingDeformTrace: A Deformable State Space Model with Relay Tokens for Temporal Forgery Localization
Temporal Forgery Localization (TFL) aims to precisely identify manipulated segments in video and audio, offering strong interpretability for security and forensics. While recent State Space Models (SSMs) show promise in …
Long-range modeling