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 137
A Valid Watermark Is Not a Valid Identity: Spatial-Spectral Adversarial Face Evasion with Watermark Preservation
Facial image watermarking can support traceability and certification in biometric pipelines, but provenance or manipulation detection alone does not guarantee reliable biometric identity.Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study
Synthetic-aperture imaging (SAI) removes occluders such as foliage by integrating many views of a scene along a camera path.Beyond Static Cues: Unified Dynamic Detection of MLLM Backdoors via Dual-Flow Trajectory Analysis
Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a formidable challenge.Read, Parse, Describe: Unified Document Parsing with Visual Element Description Generation
Document understanding systems are typically evaluated as separate components via layout analysis, optical text recognition, reading-order prediction, and image captioning.InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views
Feed-forward Gaussian reconstruction builds 3D scenes directly from input images for novel view rendering, but learning Gaussian attributes from predicted geometry for high-quality rendering under…NeuroDETR: Multiscale Discrete Spatiotemporal Tokenization for Asynchronous EEG Event Detection
Asynchronous EEG event detection supports practical brain-computer interfaces by identifying event classes and temporal boundaries directly from continuous recordings without predefined event…ReferFlow: Beyond Final-Target Localization for Complex Referring Expressions
Multimodal Large Language Models have made significant progress in referring expression comprehension (REC), yet most REC benchmarks still focus on final-target localization.Look Before You Restore: Learning to Predict Before Acting for Agentic Image Restoration
Agents for mixed-degradation image restoration typically learn what a tool does to an image only after running it: failed calls waste computation and harmful outputs go unnoticed until too late.STP-GUI: Spatially-Aware Token Pruning for Efficient Web-GUI Agents
With the rapid development of vision-language models (VLMs), Web-GUI agents have achieved promising performance in interacting with real-world interfaces through screenshot-based grounding.Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT
Anatomical labels help 3D Gaussian splatting preserve vessels in cinematic renderings of CT, but the representation is still found by optimising each patient's scene, where densification decides…Cortex: Consolidating Context into Parametric Memory
Context can improve large language model performance, but these gains may be lost after context removal.Hybrid supervised instance segmentation by learning label noise suppression
To reach top accuracy, current fully supervised instance segmentation methods severely rely on large-scale pixel-wise labeled datasets.Infant Fingerprints: Quality Assessment & Recognition
Infant fingerprint recognition is hindered by a combination of physiological characteristics, such as small ridge width and spacing, and acquisition challenges that include involuntary motion, skin…Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR
Character Error Rate (CER), the standard metric for OCR and vision-language models (VLMs), charges a typo as much as a wrong name.Quantifying privacy risks in foundation model representations of brain MRI
Pretrained representations are increasingly used to share and reuse information from medical images without exposing the original scans, but it is unclear how much patient-specific information these…OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segmentation
Low-light video processing remains an underexplored problem in computer vision, primarily due to the scarcity of high-quality ground-truth data.VascuSR: Iterative Anatomy-Aware Diffusion for CT Super-Resolution
Generative super-resolution (SR) can recover sharp detail in computed tomography (CT) images from severely downsampled observations, but the missing high-frequency content is not uniquely determined…ActiveEvidence: Decision-Focused Evidence Graphs with Verifiable Acquisition Gaps
A multimodal agent must decide whether visual evidence is worth acquiring, which candidate or resolution to query, and when further interaction can no longer change its decision.Generative Representation Learning for Scalable Latent Tokenization
We introduce an approach for self-supervised representation learning designed to be used as a tokenizer for generative modeling.PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis
Multimodal code intelligence connects the symbolic world of programs with the visual world their execution creates.