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.
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Newest papers, page 37
Vision-Language Models Are Joint Denoisers in Robotic Action Generation
Diffusion-based vision-language-action (VLA) models cascade pretrained vision-language models (VLMs) with diffusion action experts, but typically restrict the VLM to providing static conditioning.Modeling Fat-shift for Improved Head Segmentation from MRI Scans using a Probabilistic Model
Personalized computational head models for biophysical simulations rely on accurate whole-head segmentations from T1-weighted (T1w) magnetic resonance imaging (MRI) scans.Reproducing INP-Former: Reconstructing Intrinsic Normal Prototypes for Industrial Anomaly Detection
We reproduce the central claims of INP-Former, a reconstruction-based method for multi-class industrial anomaly detection.Context-Shielded Backdoor Attack against Large Vision-Language Models
Large vision-language models (LVLMs) routinely use inference-time visual-token compression to prune hundreds of patch tokens down to a compact budget.StreamClarify: Proactive Clarification for Grounded Streaming Video Question Answering
Streaming video question answering (QA) requires real-time reasoning over continuous video streams under strict latency and active-context budgets.DriftingPlanner: Drifting Generative Models for One-Step Trajectory Planning in End-to-End Autonomous Driving
End-to-end planners decode the ego trajectory either by coordinate regression, which is fast but blends plausible maneuvers into one trajectory that may follow none of them, or by diffusion and flow…[Re] Pure Noise to the Rescue of Insufficient Data
We examine the main claims of Zada, Benou, and Irani (2021), which states that in an image classification task with imbalanced training data, (i) using pure noise to augment minority-class images…Physics-Informed Functional Tucker Method with RKHS Factors for Sparse Spatiotemporal Reconstruction
Reconstructing physical dynamics from fixed sparse sensors and missing frames is a fundamental challenge in scientific research.An Empirical Study on Learning Rooftop Solar Potential from Satellite Imagery Directly Without Explicit Geometry
Rooftop solar potential estimation often relies on LiDAR, digital surface models (DSMs), or pipelines that explicitly reconstruct roof geometry before estimating solar potential.CompoSET: A Controlled Single-Edit Benchmark for Vision-Language Compositionality
Vision-language compositionality is the ability to identify which properties, relations, quantities, and states bind to which entities in both an image and a caption, and to match those bindings…MotorSense: A Video-EMG Dataset of Motoric Representations for Action Understanding
Computer vision models learn hand action only from its visual consequences, without access to the underlying embodied motor signals.One Verdict Is Not Enough: Regression Testing Learned World Models and Their Test Harnesses
Learned world models ship as software components whose model versions, preprocessing, and test harnesses change between releases.MATS: A Multi-Agent Framework for Controllable and Reflective Tumor Synthesis
Synthesizing realistic tumors on medical images helps address data scarcity for clinical AI.Mechanistic Interpretability for End-to-End Self-Driving
End-to-end (E2E) autonomous driving models achieve strong planning performance but remain largely opaque, limiting observability and trust.FlowMoDE: Coarse-to-fine Flow Matching for Detail-aware Sim-to-Real Monocular Depth Estimation
Monocular depth estimation is a fundamental capability for 3D spatial perception in robotic and intelligent systems.Beyond CLIP: Calibrated (Few-Shot) Defect Detection With System One Decision Models
Cameras and vision sensors are widely used for product and process inspection in manufacturing environments.Shifting Focus by Reliability: Geometric Fusion Modulation for Robust RGB-T Detection
RGB-thermal (RGB-T) object detectors combine visible and thermal imagery for robust detection, but signal corruption in either stream can substantially degrade accuracy.From Evaluation to Evolution: Benchmarking Image Editing and Evolving Image Models
Real-world image editing requires coordinating multiple visual transformations with content preservation and reference constraints, yet aggregate scores can readily obscure unmet local requirements.Beyond Scarcity: When Encoder Adaptation Is Worthwhile
Long-tailed recognition often learns a shared representation before correcting the classifier for class imbalance.TinyAstral: Transferring Self-Evolving Harnesses to Tiny Generalist Manipulation Agents
Robot agents built on vision-language models depend on both the planner and its harness: the tools, feedback, memory, and recovery logic around it.