Engineering & Signals · Interdisciplinary & Society
Image & Video Processing
The newest papers in Image & Video Processing that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
297 papers, from 4 September 2026 to 5 November 2026: 297 arXiv preprints.
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Newest papers, page 15
Recovering Biomechanical Signals from Missing Keypoints Using Temporal Interpolation in Monocular Gait Analysis
Monocular pose estimation enables low-cost gait analysis but is sensitive to missing keypoints caused by occlusion, detection errors, or efficiency-driven model reduction.Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion
Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning.Storage-Scalable Progressive Semantic Communication via Knowledge-Base Reuse
Existing knowledge-base-assisted semantic communication schemes commonly adopt either single knowledge-base quantization (SKBQ) or multi-knowledge-base residual quantization (MKBQ).Scale-Aware 3D Deep Learning for Robust Brain Metastasis Detection in Multimodal MRI
Detecting brain metastases in magnetic resonance imaging (MRI) remains challenging because lesions vary widely in size and appearance, with very small metastases occupying only a minute fraction of…Seamless Whole Slide Label-Free Virtual Staining
Label-free virtual staining offers a compelling, non-destructive alternative to standard histopathology; however, its clinical adoption is hindered by the computational bottlenecks inherent to…Leveraging Cardiac Imaging to Improve ECG-Based Detection of Chagas Disease in Resource-Constrained Settings
Chagas disease is a major cause of cardiomyopathy in Latin America.Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild
Spherical observations provide global visual context for 3D scene understanding.CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets
High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratification remains limited.AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution
Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability.Spatial Feature-wise Linear Modulation (SpFiLM) for Contrast Agent-Aware Brain Parcellation
Most automated brain parcellation tools are developed and validated on T1-weighted (T1w) MRI.Cross-modal learning for SAR target recognition using optical vision foundation models
Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather operating capabilities.Foundation Models for Generalizable Semantic and Goal-Oriented Communication
Semantic and goal-oriented communication is increasingly studied for 6G, but generalization beyond seen data remains a key weakness under tight rate budgets.MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting
High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and for CT, radiation dose.Spatial Attention Supervision for Defect Localization: Exploiting Ground-Truth Masks as Training Signal in Diffusion-Augmented Defect Detection
Ground-truth defect masks in industrial inspection datasets are typically reserved for evaluation.Cross-dataset transportability of pediatric chest X-ray deep learning across three countries: discrimination, calibration, operating-point failure, and limited-label recovery
Background and Objective: External evaluation of medical-imaging AI is often collapsed into discrimination.Real-World Multi-Modal and Longitudinal Lung Cancer Dataset
Multi-modal learning has demonstrated strong potential in medical applications by integrating heterogeneous data sources such as medical imaging, clinical records, and genomics to improve predictive…ViT3Flow: A Test-Time Training Transformer MeanFlow for Postoperative Radiograph Synthesis in Scoliosis
Predicting postoperative spinal morphology from preoperative radiographs could provide valuable support for scoliosis surgical planning, but remains challenging because surgical correction induces…