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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 39
Beyond Trial-and-Error: A Geospatial-Guided Active Reasoning Framework for Robust Aerial Vision-and-Language Navigation
Aerial Vision-and-Language Navigation (VLN) requires UAVs to locate language-specified goals in large-scale urban environments, where objects often appear small and visually ambiguous from…BDNet: Fast-slow thinking is all you need
We present BDNet, a hierarchical image-classification backbone built around fast image features and slow statistical references.VariaFlow: Uncertainty-Aware Flow Matching for Unsupervised Anomaly Detection
Reconstruction-based anomaly detection no longer fails at reconstruction.VoxLution: Evolving Voxels for High-Fidelity 3D Scene Generation
High-resolution 3D indoor scene generation is crucial for immersive applications such as virtual reality, spatial computing, and robotics simulation.Parameter-Efficient Fine-Tuning of Transformer Encoders for Audio-Image-Symbolic Music Retrieval
Score-based multimodal music retrieval requires representations that are both discriminative within each modality and compatible across audio recordings, sheet music images, and symbolic scores.TACO: Trajectory-Aware Curvature Observation for Memorization Localization and Mitigation in Diffusion Models
Text-to-image diffusion models can reproduce memorized training content within localized image regions, making precise localization essential for targeted mitigation.TopoHyperClinicalGraph: A Geometry and Topology-Aware Multimodal Framework for Cancer Survival Prediction
We developed TopoHyperClinicalGraph, a multimodal framework combining hyperbolic tissue geometry, persistent topology and clinical graph learning for cancer survival prediction.Scout-Refine-Correct: Teaching Flow Models to Refine Their Own Samples
The quality of image generation models trained with diffusion or flow matching is largely fixed by the training budget: at inference, the only available lever is the number of sampling steps, and…DrawSplat: Atlanta World-Guided Implicit Gaussian SLAM for Indoor Reconstruction
RGB-D SLAM requires accurate online tracking, high-quality rendering, and geometrically consistent reconstruction.Attention Maps Know When to Think: Training-Free Difficulty-Aware Chain-of-Thought for Reasoning Segmentation
Chain-of-Thought (CoT) prompting has become a standard reasoning strategy in Multi-modal Large Language Models (MLLMs), showing strong performance in complex vision-language tasks such as reasoning…GRIT: Gradient Masking for Visually Misgrounded Tokens in Text-Rich Reasoning
Reinforcement learning with verifiable rewards (RLVR) has recently been extended to vision-language models (VLMs), yet its effectiveness remains limited for text-rich reasoning tasks.TADP: Dual-Branch Temporally Adaptive Differential Privacy for Expression-Aware Video Anonymization
We present TADP, a temporally adaptive differential privacy (DP) framework for inference-time privacy-preserving video generation under fixed-length clip-replacement adjacency.When Depth Lies: Benchmarking Vision-Language Models on Mirror-Induced RGB-D Ambiguity
Vision-language models (VLMs) have made significant progress in spatial reasoning, particularly by integrating RGB images with depth data, which is often assumed to faithfully reflect physical…Enhancing Medical Lesion Segmentation via Several Simple Modules
This work introduces three lightweight enhancement modules for medical lesion segmentation to improve clinical applicability, particularly under data-scarce and computationally constrained…OpenVIO: A Versatile Open-Source Visual-Inertial Odometry System
Visual-inertial odometry (VIO) is a fundamental topic in robotics research.A Self-Supervised Pose Estimation Approach for Construction Machines
Pose estimation is a computer vision task used to estimate a skeleton of dynamic systems to predict future movements.OT-CAL: Optimal-Transport-Guided Adaptive Sample Selection for Efficient Visual Learning
Deep neural networks for image recognition are typically trained using mini-batches, with a forward pass to compute predictions and losses followed by a more computationally expensive backward pass…Retrieval-Augmented Initialization with Dual-Guided Inversion for Flow-Based Inverse Problem Solvers
Flow models have recently emerged as powerful generative priors for solving inverse problems.Nereus: A Large-Scale Underwater Dataset for Fine-Grained Attribute Understanding and Grounded Counting Perception
Underwater imagery records rich ecological information and supports applications such as science communication, fishery monitoring, ecological conservation, and oceanographic research.SAR-TS-BERT: Physics-Guided Self-Supervised Pre-Training With Polarimetric Features for SAR Time-Series Crop Classification
Multitemporal synthetic aperture radar (SAR) imagery provides continuous, cloud-free observations of crop phenology for agricultural monitoring in cloudy and rainy regions, yet high-accuracy…