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 2
Action-Conditioned VLM Monitoring for Autonomous Vehicle Semantic Anomalies
We study action-conditioned monitoring of autonomous-vehicle behavior in semantically unusual driving scenes.OptIMerge: Optimization-Based Merging of Diffusion Models
The arithmetic merging of weights from multiple task-specific models fine-tuned from a shared base model, commonly known as model souping, has emerged as a popular strategy for multi-task learning…Training-Free Predictive Spatio-Temporal Token Pruning for Few-Step Autoregressive Video Diffusion
Few-step autoregressive (AR) video diffusion models generate videos chunk by chunk and have made efficient video generation practical.Improving Long-Tail Detection via Layout-Instruction Conditioned Diffusion Synthesis
Synthetic data from diffusion models can improve object detection, but long-tail performance is still limited by scarce rare classes and inflexible conditioning (e.g., text-only or layout-only…MetricTrail: Revisiting the Power of Metric Depth and Local Optimization for Long-Sequence Streaming 3D Reconstruction
We present MetricTrail, a streaming system for accurate camera motion estimation and dense reconstruction from long monocular videos.Guidance Is a Field, Not a Scalar: Interval-Integrated Classifier-Free Guidance for One-Step Video Generation
One-step generators built on MeanFlow synthesize a video in a single function evaluation, yet inherit a rigid treatment of classifier-free guidance (CFG): the guidance scale is frozen during…Integrating Learned Priors through Prior-Space Reparameterization for Physically Based Inverse Rendering
Physically based inverse rendering decomposes appearance into materials and illumination, an ambiguous problem for which learned material predictions provide useful prior information.Georeferenced Cross-View 3D Reconstruction from Ground and Satellite Images
Georeferenced 3D reconstruction from ground images requires recovering not only the local scene geometry, but also localizing every camera center and 3D point in a geographic coordinate frame.Subspace Learning with Outlier Exposure for Out-of-Distribution Detection
Out-of-Distribution (OoD) detection is pivotal for reliable deployments of Deep Neural Networks (DNNs), aiming to distinguish anomalous samples from the In-Distribution (InD) data in training.TACT-KV: Tri-Axis Cosine Transform for Compressing Volumetric KV Caches in Medical VLMs
Vision-language models (VLMs) applied to 3D medical scans face a structural memory wall.FisherDistill: Diffusion Distribution Distillation via Closed-Form Fisher Critics
Recent advances in diffusion distillation have enabled high-quality image generation in only one or a few network function evaluations (NFEs).Towards Real-Time Full-Waveform LiDAR Transformers via Intensity-Guided Token Reduction and Physics-Aware Augmentation
LiDAR is a critical sensor for autonomous driving and robotics, yet it remains vulnerable to adverse conditions such as fog, rain, transparent objects, and low-reflectance surfaces.TRACEMARK: Editor-Aware Watermarking for User Attribution in Text-Guided Image Editing
An image editing service records which user requests each edit, but the edited image itself does not contain this account information.Neural Image Compression with Internal-External Prior Fusion and Alignment
Existing context models for learned image com- pression rely primarily on internal priors from the current image, overlooking common patterns and typical textures shared across natural images.UniGADD: Universal Generator-Agnostic Deepfake Detector
In this paper, we introduce Universal Generator-Agnostic Deepfake Detector (UniGADD), a novel method that employs supervised learning to achieve high accuracy on known deepfake generators, while…Generator-Aligned Reward Modeling with Target-Aware Bounded Optimization for Visual Generation
Post-training aims to enhance desired attributes in visual generative models while preserving their general generation capabilities.ArtCrafter: Feed-Forward Generation of Articulated 3D Object with Analytic Joint Derivation
Articulated 3D assets are essential for robotic simulation and training, yet their generation from casual images poses a key challenge: recovering part geometry and kinematics that remain mutually…Which Objects Stay? Learning Hierarchical Persistence Beliefs for Lifelong Open-Vocabulary Object Maps
Lifelong object maps must estimate whether an object remains at its previously observed location after it leaves view.CoGenRec: A Unified Generative Framework for Complementary Vision Reconstruction
Capturing scenes with extreme motion and high dynamic range is fundamentally constrained by trade-offs among temporal resolution, spatial detail, signal-to-noise ratio, and dynamic range under…Egocentric Action Recognition with Objects and Vision-Language Affordances
Action recognition, and more specifically egocentric action recognition, is a core task in computer vision, with applications such as monitoring the daily life activities of elderly people and task…