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 8
PathoS2VD: From 2D Histopathology to Pseudo Z-Stack Representations
For decades, diagnostic pathology has relied on thin two-dimensional (2D) tissue sections, despite biological tissues exhibiting inherently three-dimensional (3D) morphological organization.Clips2Story: Training-Free Video Storyboarding and Editing Using Multimodal Retrieval-Embedded Generation
Video editors often work with large collections of fragmented footage and must select and organize relevant clips into a coherent story.FedIA: Instance-Aware Cross-Modal Representations for Federated Prompt Learning
Federated Prompt Learning (FPL) enables parameter-efficient adaptation of pre-trained Vision-Language Models across decentralized clients without exchanging raw data.Intra-Architecture Source Attribution for Stable Diffusion: A New Task with Benchmark Dataset and Baseline
Designing systems that attribute a generated image to its source model has lately become a major area of AI research.MotoVerse: A Benchmark for Predictive Perception of Motorized Two-Wheelers in Dense Unstructured Traffic
Motorized Two-Wheelers (MTWs) dominate personal transport across much of the Global South, yet remain largely overlooked in predictive perception research for autonomous driving and ADAS.ChanSFormer: A Channel Agnostic Vision Transformer for Multi-Channel Cell Painting Images
High-content multi-channel imaging, from Cell Painting assays to remote sensing, is central to modern scientific pipelines.METRIC-GS: Selective Metric-Scale Estimation for 3D Gaussian Splatting
A 3D Gaussian Splatting (3DGS) reconstruction inherits arbitrary units from structure-from-motion, so it cannot be measured or used to place AR content until someone supplies a scale.USI-Brain: Enhancing Underwater Spatial Intelligence via Spatial Data-Driven Vision-Language Modeling
Underwater spatial reasoning depends on object boundaries and geometric cues that are obscured by scattering, color distortion, and low visibility.UniRestorer++: Scalable Universal Image Restoration with Multi-Granularity Degradation Modeling
Universal image restoration aims to handle diverse degradations within a single model, but a reliable scaling strategy remains underexplored.DeepfakeGenome: Toward Next-Generation Deepfake Attribution
In recent years, AIGC technologies are capable of generating hyper-realistic forged facial images, posing severe threats to facial security safety.RI-Prune: Relation and Information Aware Visual Token Pruning for Multi-Image Vision-Language Models
Large vision-language models (LVLMs) have recently been extended to handle multiple input images, but this extension dramatically increases the visual token budget, making visual-token pruning not…SVGFaith: A Two-Layer Meta-Evaluation of Faithfulness Metrics for Text-to-SVG Generation
Text-to-SVG systems are commonly evaluated by applying raster-image metrics to rasterised outputs, yet whether these scores capture fine-grained prompt faithfulness remains unclear.TouchéWorld tech report : Towards Online Unified Camera--Hand Exploration in Generative Worlds
Recent video world models allow users to explore generated environments through camera navigation.RouTex: Multi-reference 3D Texture Generation by Reprogramming Rotary Position Encoding
While single-image 3D texture generation has advanced significantly, conditioning texture synthesis on multi-view reference images remains largely under-explored, despite its necessity for resolving…SleuthVLM: Do We Really Need Audio-in-Video for Omni Video Understanding?
Omni models answer questions about videos by jointly processing sampled frames and audio in one turn, with progress driven largely by scaling model size and omni training data.GeoBiaset: A Counterfactual Benchmark for Demographic Bias in World-Level Geolocalization
World-level image geolocalization is an increasingly important task, yet the biases of current models remain poorly understood.STARE: Scene Text-Aware multimodal Retrieval for Everyday objects
In this study, we focus on service robots that retrieve and transport everyday objects based on free-form instructions that may refer to visual features and scene text.Drift-adaptive Representation Preservation for Domain-Incremental Learning
Pretrained vision models provide strong general-purpose representations, but in Domain-Incremental Learning (DIL), where the input distribution changes sequentially, adapting to new domains often…Many Pixels, One Composition: Self-Supervised Spectra for Specimen-Level Prediction
Can hyperspectral (HS) imaging be used to predict the elemental composition of physical specimens found on the Earth's surface?XuanJian-DINOSAR: A SAR Foundation Model Based on Global and Local Semantic Consistency
Self-supervised pre-training on synthetic aperture radar (SAR) imagery enables transferable representations, but the optical-SAR domain gap and speckle perturbations limit representation stability.