AI & Machine Learning · Computer Science & AI
Computer Vision
The newest papers in Computer Vision that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 29 September 2026 to 5 November 2026: 4,999 arXiv preprints and 1 OpenAlex record.
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Newest papers, page 122
Beyond Multi-Stage Pipelines: A Label-Correlation Ensemble for Multi-Label Retinal Fundus Disease Classification
Retinal fundus images frequently carry more than one disease, and public fundus datasets are heterogeneous and severely long-tailed.MTEdit: Packed Trajectories Beat Rollouts for Multi-Turn Image Editing
Multi-turn image editing aims to modify an image according to a sequence of instructions, making it better aligned with human-AI collaborative creation than single-turn editing.A Paired RGB-Sonar Dataset for Fish Monitoring with Consumer Sonar
Imaging sonar enables underwater observation in conditions where optical imaging is ineffective due to darkness and turbid water.Video Diffusion Avatars: Taming Video Diffusion Models into Controllable 3D Avatars
Video diffusion models (VDMs) trained on internet-scale data encode a rich prior on appearance, motion, and physics that is difficult to replicate with explicit 3D rendering and costly 3D data…The Collection of a Real-World, Large-Scale Dataset for Automated Skill Evaluation in Central Line Dressing Change
Central line-associated bloodstream infections (CLABSIs) remain a major source of preventable morbidity and mortality in healthcare settings.Persistent Planar Memory for Video World Models
Video world models that generate and explore environments at scale need a persistent 3D memory of what they have produced.StopWatch: Goal Grounding for Object-goal Navigation
Pretrained VLMs bring rich world knowledge and semantic priors to object-goal navigation, and fine-tuning a VLM into a navigation policy has become a common recipe.Rethinking the design space of Vanilla Pixel Diffusion Transformers
Pixel-space diffusion models have recently re-emerged as a compelling alternative to latent diffusion, avoiding the lossy latent bottleneck and separately trained autoencoder.Learning to Correct Geometry in Generated Videos
Generated videos often lose geometric consistency under camera motion: structures warp under viewpoint change, parallax becomes inconsistent, and smooth camera movement may collapse into shot-like…CLARO: Clutter Aware Robot Orchestrator for Open-Vocabulary Grasping using VLM Agents
Robots that follow natural-language instructions unlock a wide range of autonomous applications in households, warehouses, and labs.DinoMUSE: A DINOv2-guided Framework for Unsupervised Lateral Motion Estimation in Ultrasound Elastography
Quasi-static ultrasound elastography (USE) is a non-invasive imaging method for assessing soft tissue mechanical properties.ProtoGTX: Prototype-Aligned Graph Transformer for Explainable Whole-Slide Image Analysis
Deep learning has achieved strong performance in computational pathology, but explaining whole-slide image (WSI) predictions remains challenging.SynerGest: Temporal-Spatial Synergistic Gesture Generation for Dyadic Conversations
Co-speech gesture generation in dyadic conversations for creating immersive virtual avatars remains highly challenging.Implicit Neural Models for Direct Multi-Shell Diffusion MRI Signal Estimation
Diffusion magnetic resonance imaging is a noninvasive technique that is sensitive to the motion of water molecules in human tissue.Benchmarking and Improvement of Artifact Segmentation Methods in H&E-Stained Whole Slide Imaging
Technical artifacts introduced during tissue preparation or slide scanning remain a major obstacle to developing robust computational pathology algorithms for hematoxylin and eosin (HE)-stained…GliomaINK: A Tumor and Anatomy Conditioned Flow Matching Framework for 3D MRI Sequence Synthesis in Glioma Patients
Incomplete multiparametric MR examinations limit glioma characterization and downstream AI tools.LUMINR: Intensity-conditioned Meta-learned INRs for Accelerated Medical Image Registration
Implicit neural representations (INRs) have been applied to deformable image registration, where a lightweight network maps a spatial coordinate to a deformation vector.Generative Text Modelling and Language-Guided Visual Attention for Deciphering Palimpsests
Recovering obscured text in palimpsests, i.e. the manuscripts where the original writing (under-text) was erased and overwritten for reuse, is vital for preserving lost information.OrTeN: Neural Inverse Graphics for Joint Terrain and Line-scan Camera Trajectory Reconstruction
Digital terrain maps (DTMs) are used for landing site selection, terrain-relative navigation, and geological analysis in planetary exploration.BiNar: Bitstream Native Restorer for Bitstream-corrupted Image Restoration
Bitstream-corrupted image restoration (BCIR) aims to reconstruct faithful images from corrupted compressed bitstreams.