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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: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 231
DC-SAE: Deep Compression Semantic Autoencoder for Faster Diffusion Convergence
High-compression tokenizers are essential for scaling latent image generative models.Emergent Multi-View Geometry Through Self-Distillation
Over a century ago, Henri Poincaré argued that a motionless observer cannot acquire the notion of space.The Planning Limits of Latent World Models
World models offer a promising way to help robots understand how the physical world evolves and plan complex behaviours through imagination.Universal Cross-Prompt Adversarial Attacks on Promptable Concept Segmentation
The Segment Anything Model (SAM) achieves remarkable performance in visual segmentation.PLRS-IC: A Dual-Calibration Framework for Chest X-Ray Vision-Language Alignment
Fine-grained vision-language alignment in chest radiography enables zero-shot classification, grounding, and segmentation without task-specific annotations.MegaAvatar: Controllable Talking Avatar Generation
This report presents \textbf{MegaAvatar}, a controllable talking avatar generation framework built on top of the Wan2.2-TI2V-5B model.BMASH: Ball-Motion-Aware Soccer Header Spotting
Recent advances in computer vision have made broadcast sports videos increasingly useful for event analysis, performance assessment, and player-safety applications.Rethinking Generative Image Compression at Extremely Low Bitrates
Generative image compression produces visually plausible reconstructions at low bitrates, yet their behavior as the rate approaches zero remains largely unexplored.MotionWeave: Learning Motion-Centered Future Dynamics for Vision-Language-Action Policies
Vision-Language-Action (VLA) models have recently incorporated world models to provide richer dynamic supervision beyond sparse action labels.TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning
Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce.Rethinking Multi-Image Re-Representation in Multi-Image Understanding
Multi-image understanding requires MLLMs not only to recognise the content of individual images, but also to organise visual evidence distributed across them.COBICount: Separating Object and Background Responses for Remote Sensing Object Counting Without Training on Target Data
Remote sensing object counting estimates how many buildings, vehicles, or ships appear in overhead images.Beyond the Current Scene: Event-Referential Grasping with Active View Selection
A robot that observes people interacting with objects should be able to carry out later requests that refer back to those interactions.EgoTools: Towards Tool-Centric Reasoning in Real-World Egocentric Videos
Real-world embodied tasks, from everyday activities to professional procedures, require agents to act under physical constraints while tracking evolving object and task states.InfoAgent: Traceable Generation and Repair of Evidence-Grounded Infographics
Reliable infographic generation requires facts, symbols, and visual relations to remain consistent through rendering and revision.UniWAM Technical Report: Unified Mobile Manipulation via Mixed-Stream World-Action Modeling and Manipulation Anchor Pose Supervision
Mobile manipulation requires precise navigation to a manipulation-ready pose followed by reliable object interaction.PCB-MC: Missing Component Analysis in Printed Circuit Boards
Detecting missing components on printed circuit boards (PCBs) differs fundamentally from conventional object detection, as the model must localize components that are not present.Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification
Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis.CAST: Causal Advantage-Structured Training with Spatially Grounded Compositional Rewards for Diffusion Models
Online reinforcement learning has been extended to flow matching for diffusion model (DM) image generation.ResARC: Residual-Aware AutoRegressive Coding for Ultra-Low Bitrate Image Compression
Progressive autoregressive image codecs provide an appealing paradigm for generative compression by quantizing continuous latents into discrete tokens, transmitting coarse-to-fine prefix tokens and…