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 172
IntrinSync: Joint Intrinsic Decomposition and Reciprocal Rendering
Inverse rendering decomposes an image into intrinsic properties such as appearance, illumination, geometry, and material, yet these properties are inherently interdependent.ActiveMedAgent: Cost-Aware Trajectory Learning for Multimodal Medical Diagnosis
Clinical diagnosis is inherently sequential: clinicians escalate from cheap to costly tests only when additional evidence is expected to resolve diagnostic uncertainty.Improving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery
Single-image nutrition estimation can fail silently when visible foods are missed.SP-DocReader: Difference-Aware Self-Play for Precise Document OCR
Accurate page transcription remains difficult for vision language models under limited input and training budgets.A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation
Video anomaly detection (VAD) is a fundamental and safety-critical task in computer vision.CARE: Constrained Attention Refinement for Fine-Grained Visual Classification via Teacher-Student Distillation
Fine-grained visual classification requires models to recognize subtle local traits while exposing the visual evidence behind their predictions.LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs
Lifelong editing of LLMs requires storing thousands of edits after acquisition.VGGTWorld-VLA: Intent-Conditioned 3D World Evolution for Autonomous Driving
VGGT provides a strong foundation for geometry-centric world models by recovering unified 3D scene geometry from visual observations.AutoAdapt: Reliable Few-Shot Adaptation under Clinical Distribution Shifts
Large pretrained clinical models provide a practical way to reuse learned prior knowledge across hospitals by adapting models to them.VAMR: Multi-Question Agentic Reasoning for Efficient Long-Form Video Understanding
Long-form video understanding often involves multiple questions about different aspects of the same recording.IntactWorld: Joint World Modeling with Intact Features
While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic.Multimodal Remote Sensing Image Registration: A Comprehensive Review, Challenges and Prospects
Multimodal remote sensing image registration is a crucial prerequisite for the collaborative processing and downstream application of remote sensing data, such as image fusion, change detection, and…MATE4D: Matrix-Guided Editable 4D Generation from a Single Image
Generative models have rapidly pushed content creation be-yond 2D imagery toward dynamic 3D and 4D scene synthesis.WorldFact-Bench: Beyond Image-Internal Plausibility to Image-World Consistency
Advances in image generation have made visual authenticity increasingly difficult to assess.RGBD-to-3D Object Mesh Refinement via Depth Matching and Symmetry Propagation
Single-view 3D reconstructors often produce plausible meshes that disagree with the input view, especially near depth discontinuities and self-occlusions.OmniDex: Scaling Dexterous Hand Grasping to Diverse Cluttered Scenes
Dexterous grasping is the foundational primitive in embodied AI, demanding massive data to train robust models.3DTexMOR: 3D Gaussian Multi-Object Removal via Texture-Space Inpainting
3D object removal aims to remove target objects from reconstructed scenes and complete the geometry and appearance of occluded regions.Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study
Representation structure is crucial for understanding Vision Transformer (ViT) architectures and their generalization behavior.GATOR: Generative and Agentic 3D Object Reconstruction From Casual Images
Reconstructing complete, scene-aligned 3D objects from casual images requires integrating sparse, uncertain observations and inferring surfaces hidden by occlusions.How Firm Should a Grasp Be?
An ideal robot grasp is firm enough to securely handle an object, yet gentle enough to avoid damaging it.