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Computer Vision
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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 212
Scale-Recursive Rectified Flows for Few-Step Precipitation Ensembles
Fine-resolution precipitation estimates support flood risk assessment and water management, but coarse satellite products cannot resolve rainfall within each grid cell.Imagine the Future, Internalize the Gist: Efficient VLA Reasoning via Internalized Spatiotemporal Imagination
Vision-language-action (VLA) models increasingly incorporate intermediate reasoning to improve robotic manipulation, yet existing approaches primarily reason about observed states without explicitly…Capturing Dynamics: The 4D Facial Expression Intensity Dataset
The estimation and analysis of facial expression intensity play a crucial role in affective communication and human-computer interaction.SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching
Diffusion-based world models enable high-quality interactive environment generation but suffer from substantial inference overhead due to repeated Transformer evaluations during denoising.CHASE-VLA: Post-Training Quantization Framework for Vision-Language-Action Models with Chunk-Aware Scale Estimation
Vision-Language-Action (VLA) models map visual observations and language instructions to continuous robot actions, but a diffusion-based action expert (AE) poses a key challenge for low-bit…One Photon, Many Worlds: Posteriors and Predictions with Single-Photon Cameras
Single-photon avalanche diode (SPAD) cameras operate fundamentally differently from conventional cameras due to their photon-counting nature.GeoScaffold: Learning Compact Geometric Latents via Reconstruction for Efficient Vision-Language Navigation
Recent vision-and-language navigation (VLN) systems increasingly adopt streaming Video-LLM policies that map egocentric RGB observations and instructions directly to low-level actions.Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis
Vision-language models such as CLIP exhibit strong semantic generalization, but remain limited in fine-grained visual perception.SymRegFlow: Symmetry-Regularized Flow Matching for Video World Models
Flow-matching-based multi-view world models generate realistic videos, but are commonly restricted to fixed camera rigs.Correcting Guided Diffusion Trajectories with Spectral Alignment
The practical success of conditional image generation hinges on fine-grained differences in condition alignment and visual fidelity.FiberGeoText: A Vision-Language Model for Population- Level Organization of Superficial White Matter
The superficial white matter (SWM), a critical brain region for cognition across the lifespan and brain disease, contains abundant short-range association fibers whose organization remains…TRAC: Trajectory-aware Reuse and Adaptive Correction for Efficient Autoregressive Video Generation
In this paper, we present trajectory-aware reuse and adaptive correction (TRAC), a training-free framework for efficient autoregressive (AR) video generation.FUSEye: Training-Light Fisheye Detection with Overlapping Views and Zero-Initialized Adapters
Fisheye cameras give mobile robots a single-sensor, low-cost view of their surroundings, yet the COCO-pretrained detectors that practitioners routinely reuse fail on them: strong radial distortion…TerrainForge: Physics-Grounded road geometry Editing for Counterfactual Autonomous Driving
Road geometry (e.g., crests, sags, and speed humps) and surface conditions (e.g., wet or icy pavement) affect how vehicles move, what drivers and onboard cameras observe, and how much clearance…FastOPD: On-Policy Distillation for Lightweight VLA Deployment
Vision-Language-Action (VLA) foundation models have scaled rapidly to enhance manipulation performance and generalizability, but this scaling incurs high computational costs that render real-world…PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation
World action models jointly learn to forecast world dynamics and predict robot actions, such that the learned internal world dynamics guide accurate actions.Seeing, Saying, but Not Using: From Reportable Spatial Facts to Usable States in Multimodal Large Language Models
A multimodal large language model that correctly reports a spatial fact does not necessarily use that fact in subsequent reasoning.Found but Not Read: When Extracted Text Closes the Retrieval-Reading Gap in Document Vision-Language Models
Retrieval-augmented document question answering assumes that once the right page is found, a vision-language model (VLM) can read it.Revealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking
Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable deployment.ViTok: Improving Dense Semantics in AM-RADIO-Style Multi-Teacher Distillation with PHI-S and Masked Image Modelling
We study how to consolidate the current VITOK progress into a single multi-teacher distillation recipe that jointly preserves global recognition and dense semantics.