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.
Get the few papers worth your time in Computer Vision every morning.
Follow Computer Vision and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 45
MOSAIC-Flow: Orthogonal-Axis and Status-Conditioned Fusion for Missing-Sequence Completion in Brain Tumor MRI
Missing-sequence completion is important for comprehensive brain tumor characterization, but cross-modal fusion can obscure sequence-specific contrast and lose fine-grained three-dimensional tumor…ROAD: Modern Adversarial Training for Simple One-Step Distillation at Scale
One-step distillation turns pretrained diffusion models into fast generators, but strong results often require substantial training machinery and compute.Comprehensive empirical evaluation of feature extractors in computer vision
Feature detection and matching are fundamental components in computer vision, underpinning a broad spectrum of applications.BEACON: Distilled Begin/End-Aware Structured Decoding for Continuous Sign Language Segmentation
In segmentation-based continuous sign language recognition, an untrimmed video is first partitioned into lexical units; segmentation is therefore a means to an end---downstream recognition.DOSE: Dominance-Guided Ordinal Severity Estimation from Sparse Relative Annotations
Medical severity estimation commonly relies on absolute grade annotations, which are fundamentally ordinal, yet existing methods often treat the grades as independent categories.TactoHand: Learning Geometry-Based Dense Hand-Surface Interaction Fields from Video
Understanding how humans interact with the world requires a representation of physical interactions at the hand surface.Operator-Aware Posterior Sampling for Multivariate Weather Downscaling
Statistical downscaling is the task of reconstructing high-resolution meteorological fields from coarse inputs.GC-LIF: Spiking Group-Equivariant Neural Network With Group-Coupled Membrane Dynamics
Spiking neural networks (SNNs) promise event-driven, low-power inference, but on vision tasks they still acquire rotation invariance only through data augmentation.Evaluating Cultural Knowledge Editing in Vision-Language Models
Current Vision-Language Models (VLMs) frequently fail to recognize culture-specific concepts, especially from underrepresented regions.DiFuse: Fusing Native Diffusion Representations for Spatial Reasoning in Unified Multimodal Models
Unified multimodal models (UMMs) jointly support visual understanding and image generation, yet information flow between these two capabilities remains largely asymmetric: understanding…UniTele: Learning Device-Conditioned Degradations for Unified Smartphone Telephoto Super-Resolution
Super-telephoto imaging on mobile phones suffers from complex, device-dependent degradations that are poorly captured by conventional handcrafted pipelines.FutureWorld: A Plug-and-Play Causal Next-State Predictor for Interactive Video World Exploration
Interactive video world models aim to follow user actions while maintaining scene consistency over extended interactions.Intrinsic Distribution Matching
One-step and few-step text-to-image generation must accurately render the details specified in the prompt despite limited opportunities for refinement.Where Do Vision Language Models Fail at 3D Reasoning?
Vision-language models can get individual judgments right while struggling to recover and consistently use the exact properties of a 3D object.FlexTry-On: A Time-Efficient Framework for Multi-Scenario Virtual Try-on
Virtual try-on has achieved remarkable progress in recent years, yet most existing methods are designed for a specific scenario, such as cloth-to-person or person-to-person try-on, and often require…Annotation-Free Representation Learning for Polyp Retrieval in Colonoscopy Videos
Colonoscopy is inherently comparative: reliable visual assessment of polyps often depends on complementary views acquired under different viewpoints and imaging conditions.Look at Where You Think: Localization-Head Alignment for Fine-Grained Perception in Thinking VLMs
Thinking vision-language models reason for thousands of tokens, yet still miss small details in high-resolution images.AB-Attention: Accurate Block Attention for Accelerating Video Diffusion Transformers
Video diffusion transformers generate high-quality videos, but the quadratic cost of 3D full attention dominates their inference.EditAgent: Rethinking Agentic Image Editing
Agentic image editors decompose complex requests into steps, but when a step fails, they mostly retry with the same narrow set of tools and a judge that scores each output by eye directly.Event-SAMA: Language-Grounded Video Object Segmentation on Neuromorphic Event Streams
Event cameras offer microsecond temporal resolution, high dynamic range and no motion blur, but referring video object segmentation (RVOS) lacks event-stream datasets and models.