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 149
Data-free Multistep Diffusion Distillation
One-step diffusion distillation achieves strong performance on small datasets but remains insufficient for high-resolution or complex text-to-image settings.SPELUNKA: A Framework for Finding Unanticipated Associations in Vision-Language Models
Vision-Language Models (VLMs) are the backbone of many state-of-the-art multimodal systems, but often encode spurious and harmful associations from their training data.SituHOI: Scalable Capture of Scene-Situated Full-Body Human-Object Interaction
Modeling human-object interaction (HOI) in real environments requires jointly representing whole-body motion, manipulated objects, and scene geometry, yet existing datasets trade off scalable…Meaningful Moments: A Corpus of VLM-Derived Temporal Importance Labels for Video Action Recognition
Not every moment in a video is equally useful for recognizing an action.Adversarial Robustness of Camera-Radar Sensor Fusion for Autonomous Driving
Autonomous driving (AD) relies on multi-sensor perception to interpret the surrounding environment.Removing the Compute Bottleneck for Event-based Visual Place Recognition with Spiking Neural Networks
Neuromorphic sensing and computing promise low latency and high energy efficiency for robotics, yet most event-based visual place recognition (VPR) pipelines reintroduce dense, frame-like…Hybrid Context Forests and Bilateral Viterbi Matching for 3D Rib Centerline Tracing in CT
Automatic extraction and anatomical numbering (R01-R12, L01-L12) of all 24 rib centerlines in thoracic CT is essential for unfolded rib visualization, fracture detection, and surgical navigation…From Failure Prediction to Component Selection in Semantic Segmentation
Reliable scene understanding requires deciding which predictions to trust, retain, or inspect.PIGEONS: Incremental Long-Video Captioning with Persistent Identity Gallery and Evolving Overarching Narrative Summary
Detailed video captioning has become an essential semantic interface for multi-modal understanding and generation.Regime-Aware Router Learning for Multi-Domain Medical Image Generation with Diffusion Experts
Heterogeneous medical image data motivate domain-specialized diffusion experts, but expert specialization alone does not determine how their predictions should be combined during sampling.Elephant in the Fridge: Constant-Memory Frame Packing for Long Video Understanding
Hour-long videos, streaming feeds, and movie-length content are pushing vision-language models (VLMs) past their breaking point -- the standard recipe of encoding each frame into visual tokens…Geometry-Guided Semantic Reconstruction for 3D Instance Segmentation
3D instance segmentation requires representations that are both geometrically structured and semantically discriminative.A Concept-informed Interpretable Artificial Intelligence Framework for Breast Ultrasound Diagnosis
Most existing artificial intelligence systems for breast ultrasound rely primarily on image-driven prediction, with limited incorporation of the knowledge from the Breast Imaging Reporting and Data…ProMoDD: Dataset Distillation for 3D Human Motion via Prototype-Conditioned Diffusion Models
Dataset distillation (DD) aims to retain the training utility of a large dataset in a much smaller set of examples.Omni-Modal LLMs Know More Than They Say
Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language, enabling a broader range of multimodal tasks.All-St3R SLAM: Real-time RGB Dynamic SLAM with Pixel-wise Motion Masking
SLAM (Simultaneous Localization and Mapping) is a core technology in autonomous systems that enables them to estimate their own position and build a map of unknown environments simultaneously.Unravel: Recovering an Interactive 3D Scene from a Single Image
We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable asset.Esports World Model Dataset
Interactive world models must capture how multiple participants jointly change a shared environment while observing different parts of it.Geometric Parrots: Rule Absence vs. Rule Fragility in Spatial and Physical Reasoning for Vision-Language Models
Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for example, abandoning a correct answer when…EventLens: Event-Structure Reinforcement Learning for Video Understanding
Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent.