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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 78
Cycle-of-Thought: Self-Evaluative Iterative Reasoning for Table Visual Question Answering in Document Images
Recent advances in Vision-Language Models (VLMs) have significantly improved Visual Question Answering (VQA) performance, yet their reasoning over structured content such as tables remains…Tempo-Zero: Recursive Self-Play in Executable Worlds for Video Reasoning
Video reasoning requires understanding how events unfold over time, yet videos with accurate temporal annotations are expensive to collect.PROVE: Probabilistic Visual Grounding via Patch-Level Evidence for Vision-Language Models
Visual grounding with vision-language models such as CLIP typically produces a single deterministic relevance map for an image-query pair, without indicating whether the localisation is reliable or…Learning Fine-Grained Visual Classification with Text as Privileged Information via Multimodal Distillation
Fine-grained visual classification (FGVC) requires distinguishing between highly similar categories by focusing on subtle, localized visual differences.AutoMIL: Automated Multiple Instance Learning for Whole-Slide Image Classification
Developing multiple instance learning pipelines for the classification of whole-slide images involves many interdependent design decisions and expertise in both pathology and machine learning.MDMR-Bench: A Multi-Dimensional Benchmark for Multi-Reference Image Generation
Image generation models have rapidly advanced, with many models now supporting generation conditioned on multiple reference images and textual instructions.OPTARI: An open-source software framework for clinical translation of optoacoustic imaging
Combined optoacoustic (OptA) and ultrasound imaging is a promising modality across a wide range of pathologies.Online Continual Learning in Edge-Cloud Applications
Deployed machine learning models in real-world IoT and edge/cloud systems face a critical reliability bottleneck: the requirement for online adaptation to non-stationary data streams while operating…From Perception to Pixels: Human-Derived Visually Distinct Colors for Improved Dominant Color Extraction
Dominant color extraction is a fundamental task in computer vision, with applications in design, image retrieval, and content recommendation.PathJev: Decision-Native Vision-Language Modelling for Histopathology
Vision-language models used for decisions in histopathology rarely return calibrated probabilities over the candidates a user cares about.PCFBench: How Far Can Large Vision-Language Models Go in Physics-aware Photonic Inverse Design?
Photonic crystal fibers (PCFs) underpin critical applications in telecommunications, sensing, and high-power laser delivery, yet their design remains a manual, expert-intensive process that couples…Efficient Zero-Shot Video Anomaly Detection via Signal-Aware Adaptive Fusion (SAAF)
Deploying Vision-Language Models for video anomaly detection confronts a fundamental constraint.L0-Norm-Based CycleGAN for Unpaired Brain CT-to-MR Synthesis
Computed tomography (CT) and magnetic resonance (MR) imaging provide complementary information for the brain, but acquiring both modalities is not always possible.K-CLUE: A Segmentation-to-Clustering Framework for Ki67 Cell Typing
Ki67 is a key marker of tumor proliferation in breast cancer, but its quantification from immunohistochemistry images normally depends on supervised classifiers trained per dataset.Distortion-Aware Spatiotemporal Learning for Real-Time Wide-Angle Video Rectification
While wide-angle lenses provide an expanded field of view (FoV), they exhibit severe nonlinear distortion near image boundaries, unnaturally stretching people in these regions.Augmentation Strategy for DINO in Glaucoma Classification
Self-supervised learning (SSL) offers a promising approach to medical image representation learning, yet augmentation strategies of SSL frameworks validated on natural images do not reliably…Fast and Useful: Adapting Distilled Generators for Visual Learning
Distilled text-to-image models generate images quickly, but classifiers trained on those images can perform substantially worse than classifiers trained on images from their slower base models.VERA-Hand: A Verified Multidimensional Benchmark for 2D Hand Pose Estimation in Third-Person Dynamic Gesture Videos
Hand landmarks serve as input for gesture recognition, sign language understanding, and touchless human-computer interaction.HEALPix-Based Implicit Neural Compression of Omnidirectional Images
Real-time decoding of omnidirectional images is essential for immersive virtual reality (VR) experiences.Shared Is Not Enough: Predictor Width and Factor Readability Under Masked Latent Prediction
Masked latent prediction methods such as I-JEPA aim to learn predictable features, but what determines which information they retain is less clear.