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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: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 198
Gauss-Map Variation for Image Denoising: Geometric Analysis and an Anderson--Accelerated Majorization--Minimization Method
We propose a Gauss-map variation (GMV) model for image denoising that measures the spatial variation of the tangent-plane projectors of the scaled image graph.Level-of-Token Diffusion
Image and video diffusion models allocate equal computation to every region, even when the intended scene calls for varying levels of detail.Dual-Rate Force-Image Control with Model-Based Orientation Limits for Robotic Ultrasound
Robotic ultrasound couples a high-rate contact-force loop with slower, delayed image feedback, so image-guided ultrasound probe rotation can perturb contact force before the resulting image response…Imagine to Act: High-Fidelity Data Synthesis via Image Editing World Model for Scalable GUI Agent Training
Graphical User Interface (GUI) agents have emerged as a promising paradigm for automating complex digital workflows across diverse applications.Weave Mamba Fusion: Global Cross-Scale Interaction for Lightweight Face Detection
Feature pyramid methods, from FPN to BiFPN, have achieved strong performance in face detection by fusing multi-scale features.Certification of Real Images through Calibrated Content Authentication
Generative models can synthesize high-quality inauthentic multimedia content that is already being misused at scale.fMRI-TAMCL: Text-Anchored Supervised Multimodal Contrastive Learning for fMRI-Based Brain Disorder Classification
Resting-state fMRI is important in the classification of brain disorders, but highly multimodal and exhibits strong multisite heterogeneity.Spatial Supervision Without Attribution Optimization: Improving Post-Hoc Class Activation Maps via Box-Guided Evidence Routing
Post-hoc class activation maps (CAMs) are a standard tool for inspecting the evidence behind an image classifier's predictions, yet nothing in ordinary training encourages these maps to be spatially…TasteRoute: Personalized Routing for Video Generation
Rapid progress in video generation has led to a plethora of models that differ substantially in capability and generation cost.Fitting Vision Adapters at Frontier Scales
Training a small projector between a frozen vision encoder and language model is an established approach to multimodal learning.LoDEOT: Low-Dimensional and Efficient Offset Tokens for Building Footprint Extraction from Off-Nadir Imagery
Instance-level roof-to-footprint offset (RFO) prediction is central to extracting building footprints from off-nadir imagery.End-to-End Autonomous Recursive Arborescence Deformable Flow and Non-Linear Hemodynamics for Patient-Specific Coronary Centerline Extraction
Extracting patient-specific vascular trees from volumetric medical images is fundamental to computational angiography and non-invasive hemodynamic assessment.On Hyperparameter Tuning on the Test Set
"Don't tune hyperparameters on the test set" is often stated in machine learning textbooks.Safe Image Generation via Reinforcement Learning
Recent Text-to-Image (T2I) models achieve remarkable visual image generation performance, but they can still generate NSFW (Not-Safe-For-Work) contents, including violent or explicit images.AstraSR: Real-World Thermal Super-Resolution with GPT-6 Astra
Real-world thermal super-resolution (SR) is constrained by limited sensor resolution and the difficulty of obtaining corresponding high-resolution (HR) observations for direct model supervision.Every View Counts: View-Consistent Panoptic Quality for Multi-view Panoptic Segmentation
Multi-view panoptic segmentation assigns a semantic class and a scene-level instance ID to every pixel of an unordered set of images, and recent feed-forward 3D models predict these labels for the…Prompt and Refinement: Asymmetric Mutual Learning for Infrared Small Target Detection with Noisy Labels
Existing data-driven infrared small target detection (ISTD) methods typically require large-scale datasets with accurate pixel-level annotations for model training.Beyond Transport Cost: Routing Differences between Flow Matching and Optimal Transport
In generative models, Optimal Transport (OT) is used to improve Flow Matching (FM) by reducing noise-data coupling cost.UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance
Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation.Structural Foundations of Nonlinear Systems with Unknown Inputs: The UID-Induced Normal Form and Minimal-Sensing Structure-from-Motion
This paper establishes the first general structural solution to the problem of state estimation for nonlinear systems driven by unknown inputs.