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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: 4,999 arXiv preprints and 1 OpenAlex record.
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Newest papers, page 120
The Optimal Ranking Tradeoffs Between Two Ranking Scores in Two-Class Classification
The accuracy, true negative rate (negative class recall), true positive rate (positive class recall), negative predictive value (negative class precision), positive predictive value (positive class…FlashReFocus: Interactive Image Refocusing in Seconds
Single-image refocusing changes the focal plane and depth of field of a photograph after capture.Look, Reason, Draw a Region: Recursive Refinement for Spatial Context Prediction
Spatial context prediction requires visual grounding and spatial reasoning to identify vacant regions relative to objects in a scene.CatchUp: Depth-Aware Re-Admission of Visual Tokens for Efficient Large Vision-Language Models
Large Vision-Language Models (LVLMs) repeatedly process hundreds of visual tokens across decoder layers, incurring substantial computation and memory costs.TransNSNet: A Transformer-Enhanced Multi-Scale Adversarial Framework for CT-to-PET Image Synthesis
This study investigates CT-to-PET image synthesis using TransNSNet, a Transformer-enhanced multi-scale adversarial framework.STC-MGNet: Spatial-Temporal-Channel Attention-Enhanced Multimodal Graph Network for Pedestrian Intention Prediction
Accurate prediction of pedestrian crossing intentions plays a critical role in enhancing the safety of pedestrian-vehicle interactions in autonomous driving.UniPolar: Joint Image and Polarimetric Restoration under Compound Degradations via Physical Consistency Learning
Polarimetric image restoration aims to recover polarization angle images and reliable polarimetric quantities from degraded observations.MOSS-Image Technical Report
Recent closed-source image generation systems can produce diverse visual content from simple compositions to information-dense graphics, yet open-weight text-to-image models still struggle with…FloodVLM-Pix: Language-Guided Pixel-Level Flood Understanding
As climate change intensifies, floods are becoming more frequent and destructive, making accurate flood understanding an urgent priority.LithoWorld: An Endpoint World Model for Lithography Process-Window Recovery
Lithography process drift can move a fabricated pattern outside its process window, producing unqualified scanning electron microscopy (SEM) morphology.Can We Use Saliency Maps for the Evaluation of Generative Image Models?
Evaluating generative image models remains challenging, as commonly used metrics depend on fixed pretrained feature extractors optimized for different tasks that do not always align with human…GeoReason: Bridging Logical Reasoning and Spatial Fidelity in Remote Sensing Segmentation
Multimodal Large Language Models (MLLMs) have significantly advanced instruction-driven perception through the "Embedding-as-Mask" paradigm.mmPencil: Toward Writing-Style-Independent In-Air Handwriting Recognition via mmWave Radar and Large Vision-Language Model
In-air handwriting recognition based on radio frequency (RF) signals offers a promising solution for human-computer interaction, yet existing methods are often limited by predefined writing planes…Momentum: Persistent Dynamics for Video World Models
Video world models must capture how a scene evolves beyond the current camera view to generate consistent observations when its content reappears.ShadowCast: On-the-Fly Context-Aware Shadow Augmentation for Remote Sensing Image Segmentation
Shadows cast by elevated objects alter the spectral appearance and obscure the boundaries of objects in remote sensing images, thereby degrading semantic segmentation performance.TriINR: Unsupervised Atmospheric Turbulence Mitigation with Triple Implicit Neural Representations
Atmospheric turbulence degrades image quality in long-range imaging.When Evidence Vanishes: Distilling Visual-Evidence Dependency in Medical Vision-Language Models
Compact medical vision-language models (VLMs) can answer clinical questions correctly without reliably using the image, relying instead on question wording or learned priors.TAN: A Size- and Form-Adaptive Masked-Convolution Encoder for Tissue Graphs
Tissue graphs represent histology images as graphs over tissue-conforming superpixels, which keeps homogeneous tissue regions intact instead of cutting them into rectangular patches.PONDER: Learning to Generate in the Right Order
We introduce PONDER, a method that learns in which order an image generator should fill in content and which of its earlier predictions to revise.ReVision: Reprogramming Image Generators for Dense Visual Perception
Recent image generators exhibit rich visual priors that can support dense visual perception.