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 138
Reliability-Aware Multimodal Sentiment Prediction Under Local Modality Missingness
Multimodal sentiment models are usually evaluated on complete utterances, yet streams often lose a contiguous span of text, audio, or video.Speculative Sampling in Interactive Video Generation
Interactive video generation commonly relies on small bidirectional chunks to reduce response latency.PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition
3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence in foundation models.A$^3$PreCore: Robust Rigid Registration for Native FLAIR-Space Brain-Mask Transfer
Reliable brain-mask transfer into native fluid-attenuated inversion recovery (FLAIR) space can fail when T1-to-FLAIR rigid registration is unstable.Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation
Long-form agentic video generation must turn a screenplay into shots that remain spatially and temporally consistent across nonconsecutive requests.Player-1: Learning to Play from Synthetic Experience
Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions.Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes
Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solution.Feed-Forward Multi-View Feature Coding for 3D Gaussian Splatting
Feed-forward 3D Gaussian Splatting (3DGS) methods enable efficient reconstruction of 3D scenes from sparse multi-view images in a single forward pass, without scene-specific optimization.GeoThinker-$F$: Endogenous Predictive World Representations for Fast Spatial Intelligence
Existing geometry-aware Multimodal Large Language Models (MLLMs) increasingly rely on external 3D encoders to provide structural priors, but executing these additional encoder paths at inference…DynThinker: Unifying Static 3D and Dynamic 4D Spatial Reasoning
Achieving general spatial intelligence requires a unified understanding of both static 3D and dynamic 4D.CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image Generation
We present CommerceGen-Studio, an end-to-end framework for generating commercial-grade main images for e-commerce Stock Keeping Units (SKUs).VITAL: From Visual Motion to Precise Action
World-action models aim to turn visual anticipation into driving decisions, yet typically train action experts on trajectory representations defined independently of visual dynamics.Representation Conditioning for Generation
Representation-alignment methods effectively accelerate the diffusion transformer training.Can Learning to Answer Spatial Questions Improve Novel-View Generation?
Generating novel views from limited observations requires preserving both the appearance and spatial structure of a scene.Learning Topology-Aware Representations for Mechanics-Relevant TPMS Metamaterials
Learning informative representations of mechanical Triply Periodic Minimal Surface (TPMS) metamaterials is important for mechanics analysis and structural design, yet existing methods have rarely…Orbia: Do Generated Videos Form a Consistent 3D World?
Video generators serve as interactive worlds for exploration and simulation, yet realistic and visually appealing frames do not necessarily depict a consistent 3D world.WorldCast: Exploring Intelligent Visual Generation in World State Prediction
Humans interpret multimodal observations of the world and forecast how it will evolve.Purify Before You Align: Improving Representation Alignment for Diffusion Models
Representation alignment improves and accelerates diffusion training by encouraging intermediate features to match a pretrained visual encoder.ReasonUni: Reasoning-Augmented Reconstruction Advances Unified Multimodal Models
Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs).Blame Errant Words, Not the Canvas: Defect-Aware Spatial Credit Assignment for Visual Text Generation
Recent reinforcement learning approaches have improved visual text generation, yet generated images still suffer from incorrect wording and malformed glyphs.