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 10
TSGL: Teacher-Student Graph Learning for 3DGS Compression
3D Gaussian Splatting (3DGS) is a popular representation for novel view synthesis.Joint Supervised and Self-Supervised Training with Acquisition-Robust Techniques for Accelerated 4D Flow MRI Reconstruction
4D flow MRI measures time-resolved, three-directional blood velocity but requires long acquisition times, and its diagnostic signal is carried by the phase difference \emph{between} velocity…LensBridge: Frequency-Guided Compound Degradation Adaptation for Lens Aberration Correction and Veiling Glare Removal
Simplified optical systems often exhibit residual lens aberrations and Veiling Glare (VG), resulting in spatially varying blur and contrast reduction.EgoRefine: Ego-Referenced Predictive Alignment and Trajectory-Conditioned Reliability-Aware Fusion for Asynchronous Collaborative Perception
Collaborative perception enables connected agents to share complementary observations for 3D object detection, extending sensing range and mitigating occlusion.EnergyEminence: Source-Aware Environmental Calibration and Evaluation in a Physics-Grounded Grid Digital Twin
Power-grid digital twins must combine data-driven prediction with physically meaningful state evolution while preserving the provenance of environmental observations.CAMEO: A Class-Activation-Mapped Equitable Overlay Framework for Fair and Robust Deep Learning-based Skin Condition Diagnosis
Deep learning classifiers for dermoscopic skin lesions often reach high in-distribution accuracy while quietly relying on spurious background cues such as skin tone, device vignetting, and embedded…Scalable In-Domain Self-Supervised Foundation Model for Dense Representation Transfer in High-Resolution Plant Imaging
High-resolution plant imaging enables detailed characterization of plant morphology, but dense scientific analysis remains limited by costly pixel-level annotations, large image pixel dimensions…Active Data Acquisition with Side Information via Discrete Diffusion Priors
Acquiring data is costly: higher measurement fidelity costs power and storage and risks collecting irrelevant content, while aggressive cost reduction can discard information that later analysis…RefCompose: Multi-Reference Image Generation via LoRA-Conditioned Diffusion
Filmmakers and visual artists routinely need to compose multiple references, actors, locations, props, cultural elements, into a single coherent shot, but existing tools either fail to scale past a…LoCoVSR: Local Context Diffusion Posterior Sampling for Video Super-Resolution
Video super-resolution (VSR) is an ill-posed inverse problem that aims to reconstruct a high-resolution (HR) video from a noisy, low-resolution (LR) version of it.Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling
\textit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by applying techniques from the optimal transport…Mask2Restore: Self-Supervised Ultrasound Despeckling via Inpainting
Medical ultrasound (US) is inherently degraded by speckle, a granular interference pattern that is often treated as a complex form of noise in image restoration.Image Reconstruction from Phase with Untrained Neural Priors
Fourier phase encodes important spatial image structure, but recovering an image without measured spectral magnitude requires additional constraints and leaves absolute intensity ambiguous.Learning Polarization Image Restoration with General Restoration Priors
Polarization imaging captures distinctive surface and geometric cues that benefit a wide range of vision tasks.Quantum Diffusion Models for Medical Image Analysis
Quantum Machine Learning is a novel field of research aimed at devising machine learning approaches exploiting principles of quantum mechanics, such as superposition, entanglement and interference.Enhancing Photogrammetric Digital Surface Models with Pretrained Diffusion Models and Multimodal Conditioning
Large-scale Digital Surface Models (DSMs) can be produced cost-effectively from satellite images via stereo-photogrammetry.Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learning
Congenital heart disease (CHD) is the most common birth defect, yet a large fraction of cases remain undetected on prenatal ultrasound, in part because current artificial-intelligence methods assume…MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis
In this work, we explore MammoClaw, a training-free agent framework that leverages frozen MLLMs for mammography analysis.Beyond Sparsity: Weight Location and Network Context in Pruned MRI Reconstruction
Pruning reduces the number of weights in magnetic resonance imaging (MRI) reconstruction networks.Awaken, Then Scale: Tiny Adaptation for MRI Reconstruction
Dormant Awakening (DA) specializes a magnetic resonance imaging (MRI) reconstruction model by fitting a small set of zero weights to one labeled slice.