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 102
SolarRenderer: Few-Step Generative Reference Rendering
Game engines and coding agents can specify the layout, motion, and camera of a scene, yet turning such coarse structure into realistic video requires a renderer that follows the structure and…AEON: Unifying Video and 3D World Models
Current world models for explicit world simulation typically follow two distinct pathways: (1) video generative models (e.g., Sora), which simulate realistic appearances but fail to preserve 3D…Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs
Video generation models can now depict remarkably realistic motion.Scaling in Games: Continued Pre-Training For Embodied Agents In Diverse Virtual Worlds
Scaling data, diversity and model capacity has improved embodied learning in physical environments, where diverse experiences remain grounded in shared physical laws.Different Defects, Different Effects: A Controlled Audit of Face Recognition Training Data
The development of face recognition has been strongly supported by the availability of large-scale training datasets.Motion Equivariant Convolutional LSTM: When Motion Becomes a Gauge Symmetry
Objects move, cameras pan, and weather drifts with the wind: much of what changes in sequential data is motion.Complexity-Aware Surgical Video Reasoning Segmentation with Digital Twin and Context Memory
Conventional surgical segmentation relies on closed-set categories or explicit text queries, which cannot resolve implicit queries that require reasoning about workflows, instrument functions, and…JUICE: Unified Multimodal Modeling in Pretrained Representation Spaces
Most unified multimodal models treat images and text asymmetrically: a pretrained language model generates text, an attached diffusion head generates images, and outputs that contain both are…SAIL: A Learnable Generalisation of Spatial Autocorrelation over Graph-Structured Data
In vision and scientific domains involving spatial data, a key question is whether node feature values vary independently across space or form coherent spatial structures.Register Anything Model for Generalizable and Robust Point Cloud Registration
We present Register Anything Model (RAM), a unified model for generalizable 3D point cloud registration that robustly estimates 6-DoF transformations across diverse domains spanning sensors and…WorldStream: Streaming Interactive 3D Worlds with Hierarchical Planning and Persistent State
We present WorldStream, an open-ended 3D world model with three simultaneous capabilities: it extends playable terrain beyond any pre-specified map, acts on open-ended language in the running world…HorizonComposer: Spatiotemporally Consistent Driving Video Editing with Enriched Traffic Semantics
Instruction-guided video generative models offer a scalable solution for stress-testing autonomous driving systems by simulating diverse environmental conditions.Conditional Imaging for Privacy-Preserving Visual Sensing
Conventional visual sensing faces a fundamental dilemma: information that should remain private today may need to be recovered tomorrow.Sketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis
This study proposes a sketch-to-simulation system to solve handwritten circuit diagrams.Beyond Correct Answers: How Compositional Cues Shape Visual Judgments
Visual question answering requires models to assign attributes and relations to the correct objects, a problem known as visual binding.Depth-guided Geometric Adaptation for Few-shot Image Classification
Few-shot image classification (FSIC) frequently suffers from visual ambiguity, where background clutter and RGB appearance similarities hinder discriminative feature matching in data-scarce settings.DualHeads: Reward-tilted few-step diffusion made simple
Distilled diffusion models generate high-quality images in a few sampling steps, but aligning them with task requirements and human preferences is difficult.Real2Sem2Real: 3D Semantic Augmentations for Robot Learning from a Single Human RGB Demonstration
Human video scales easily and does not need robot hardware, but existing methods require depth sensing, overlay the robot onto 2D video, or generate data only for the demonstrated objects.Policy-Mask: Budget-Aware Adaptation of Diffusion Features to Discriminative Tasks
Selecting intermediate features from a frozen diffusion model for discriminative tasks is non-trivial because the useful signal is distributed across the denoising trajectory, network depth, and…Data-Driven Glyph Positioning for Handwritten Music Synthesis
Synthesised data is a common strategy to address the lack of annotated handwritten music scores in Optical Music Recognition (OMR).