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: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 211
Investigating Spatiotemporal Redundancy in Video Transformer for Collision Anticipation
In worker-equipment proximity monitoring, video transformers are widely used for collision anticipation and have demonstrated strong performance.Probabilistic Pedestrian Forecasts from a Handheld Phone: World-Frame Heat Maps, Visual-Inertial Height Drift, and Evaluation without Ground Truth
A pedestrian with a phone could be shown where nearby people will be in the next few seconds, if the forecast stays on the ground while the phone moves, is calibrated, and needs only a monocular…ThyCLIPNet: A BiomedCLIP-Guided Lightweight Attention-Enhanced DeepLabV3+ Framework for Robust Thyroid Nodule Segmentation
Accurate thyroid ultrasound segmentation is often challenged by low contrast, speckle noise, and unclear boundaries.ARISE: Adaptive Agentic Reasoning with Image-grounded Self-Evaluation for Interpretable IBD Assessment
Inflammatory bowel disease (IBD) requires frequent imaging-based assessment, yet interpretation of modalities such as wireless capsule endoscopy (WCE) and intestinal ultrasound remains heavily…Super-Resolution in The Right Latent Space: A Frozen Vision-Foundation Substrate
In an image latent space, the embeddings of high-resolution, natural, and sharp images form a manifold.Lollypop: Camera-to-Motion-Capture Calibration Verification with a Reference Target
Camera-to-motion-capture (mocap) calibration is essential for using mocap as ground truth in robotics, AR/VR, and other computer vision tasks.KALEIDO: Input-Space Adaptation of a Vision Model for Time-Series Forecasting Through Gated Fold Geometries
Time-series foundation models buy zero-shot forecasting with large temporal corpora; a vision model needs none, since a natural image implicitly embeds the patterns a forecaster must model, and an…Active-DiNTS: Active Differentiable Network Topology Search
Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying it to 3D medical image segmentation is limited by two well-known costs, large annotation…Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness
Missing modality remains a longstanding challenge in multimodal learning.MedImageOSWorld: Benchmarking GUI Agents for Medical Image Consoles
Graphical consoles offer a practical interface for medical acquisition assistance, allowing agents to work through the controls and visual feedback used by human operators.ExStereo: Lifting 2D Vision-Language-Action Models to 3D with Explicit Stereo Representations
Three-dimensional perception is critical for robotic manipulation, particularly for high-precision tasks, as recovering metric depth and precise 3D object positions from monocular RGB observations…MOXIE: Discovering Alternative Explanations for Biomedical Image Classifiers
Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from one fixed image segmentation.DriftSR: One-Step Real-World Image Super-Resolution via Distribution Drifting
One-step real-world image super-resolution (Real-ISR) offers efficient inference, but recovering realistic and perceptually rich details often relies on score distillation or adversarial learning…RADC: Risk-Aware Dual Caching for Vision-Language Test-Time Adaptation
Cache-based test-time adaptation (TTA) for vision-language models is often hindered by background bias in global representations and unreliable entropy-based cache admission under representation…UniPro: Unified Multi-Mode Medical Image Segmentation from 2D Images to 3D Volumes via Propagation
Medical image segmentation remains fragmented along two axes: segmentation paradigms and data dimensionality.Beyond the Linear Representation Hypothesis: Non-Linear Activation Steering in Text-to-Image Models
Mechanistic interpretability often relies on the Linear Representation Hypothesis (LRH), which assumes that high-level concepts are encoded as linear directions in activation space.ROMA: LLM System for Real-World Object-Centric Multi-Sensory Active Perception
Humans inherently understand the physical world through an active process.DistScene: Object-to-Scene Distillation for 3D Scene Generation
We present DistScene, a framework for single-image compositional 3D scene generation by jointly modeling the environment and individual objects.BoT-Feedback: Grounding Multimodal Reasoning in Biomechanical Evidence for Explainable Human Action Feedback
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual understanding and multimodal reasoning, yet they remain fundamentally limited in Human Action Feedback…Event Cameras for Melt-Pool Monitoring in Additive Manufacturing: A Benchmark and a Cross-Machine Transfer Analysis
Melt-pool monitoring is central to qualifying metal additive manufacturing (AM), yet no public event-camera benchmark exists for this domain.