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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 60
CTBakeGS: training-free baking of photorealistic CT volume renderings into 3D Gaussian splats
Photorealistic volume rendering of computed tomography (CT) may convey anatomy intuitively, but it needs the CT data, dedicated software and a powerful graphics processor.When Visual Evidence Is Insufficient: How Instructions, Post-Training, and Internal Activations Shape Refusal in Multimodal Language Models
For reliable deployment, multimodal large language models (MLLMs) should recognize when an image provides insufficient evidence to answer a question and withhold unsupported answers.Segmentation Confidence for Arbitrary CNNs
Convolutional neural networks (CNN) are widely used for medical image segmentation.Representing the Unseen: Rethinking Visual Imagination for Spatial Reasoning
Visual world models increasingly support spatial reasoning by generating RGB views of unobserved states.PerceptRL: Making Visual Perception Rewardable in MLLMs from Answers to Interactions
Fine-grained visual perception remains a bottleneck during post-training of multimodal large language models (MLLMs), as perceptual errors can constrain gains from reasoning-focused optimization.How Reliable Is Individualized Functional-Network Attribution in Resting-State fMRI Cognitive Prediction in ADNI?
Individualized attribution estimates which functional networks drive a model prediction for a given subject and is often proposed as an interpretable resting-state fMRI (rs-fMRI) biomarker, but its…ALADDIN: Adversarial Latent Diffusion Distillation for One-Step Identity Swapping
Face swapping transfers a source identity onto a target image while preserving the target's pose, expression, hair, and lighting.A note on data-efficient finetuning of vision foundation models
Adapting foundation models to a new task within or beyond the training domain is the de facto standard for building specialized machine learning models.GroundControl: Satellite-Conditioned Multi-View Diffusion for Reconstruction-Free Novel View Synthesis
Multi-view or video diffusion models have recently emerged as state-of-the-art approaches for novel-view synthesis from sparse image collections.ReferStream: Interactive Subject Injection for Streaming Video Generation
Injecting new subjects naturally during streaming video generation requires integrating newly supplied visual references into the existing video while preserving established subjects and the scene.The Noise Plane: A Diffusion Bridge Across Exponent and Dispersion
Diffusion-based denoising commonly uses Gaussian perturbations, whereas sensor noise follows diverse signal-dependent statistical laws.As the Story Unfolds: Watching a Film and Identifying Characters as a Human Does
Films introduce characters incrementally as they progress.Zero-Shot Multimodal Event Spotting in Soccer Broadcasts
Automatic soccer event spotting supports highlight generation, video indexing, and sports analytics, but existing methods depend on large annotated datasets and soccer-specific training.MoI-Bench: A Benchmark for Image Generation and Editing on Mobile Devices
Developing on-device image models requires considering practical user needs, task types and device resource constraints.VideoLVR: Latent Visual Reasoning over Grounded Video Evidence
Chain-of-thought reasoning has substantially advanced video understanding in multimodal large language models (MLLMs).Perceiving and Predicting Dynamic Sports: Spatiotemporal Intelligence in Vision Models for Egocentric Tennis Video
Agile robots require spatiotemporal intelligence to interpret scenes, reason about interactions, and anticipate future events.Know, then Draw: A New Learning Paradigm for Visual Generation
Visual generation requires both high-level semantic knowledge and fine-grained pixel details.Repurposing Video Diffusion Transformers for Cross-View Temporal Object Correspondence
Cross-view object correspondence identifies the same object across views.Can Discrete Tokens Serve as Semantically Lossless Representations of Visual Signals?
Discrete visual tokens represent vision in a discrete form analogous to language, offering a native interface for multimodal modeling under a shared next-token prediction objective.ThinkWorld: World Imagination Reinforces Chain-of-Dynamics Reasoning
Vision-Language-Action (VLA) models have made substantial progress in robotic manipulation, but their generalization remains constrained by the diversity and coverage of action-labeled robot…