Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 53,511 to 53,520 of 225,548 articles

FastVMT: Eliminating Redundancy in Video Motion Transfer

arXiv Feb 5, 2026
Video motion transfer aims to synthesize videos by generating visual content according to a text prompt while transferring the motion pattern observed in a reference video. Recent methods predominantly use the Diffusion Transformer (DiT) architecture... read more 
Computer Vision and Pattern Recognition

IndustryShapes: An RGB-D Benchmark dataset for 6D object pose estimation of industrial assembly components and tools

arXiv Feb 5, 2026
We introduce IndustryShapes, a new RGB-D benchmark dataset of industrial tools and components, designed for both instance-level and novel object 6D pose estimation approaches. The dataset provides a realistic and application-relevant testbed for benc... read more 
Computer Vision and Pattern Recognition cs.RO

Visual Implicit Geometry Transformer for Autonomous Driving

arXiv Feb 5, 2026
We introduce the Visual Implicit Geometry Transformer (ViGT), an autonomous driving geometric model that estimates continuous 3D occupancy fields from surround-view camera rigs. ViGT represents a step towards foundational geometric models for autonom... read more 
Computer Vision and Pattern Recognition

A Hybrid CNN and ML Framework for Multi-modal Classification of Movement Disorders Using MRI and Brain Structural Features

arXiv Feb 5, 2026
Atypical Parkinsonian Disorders (APD), also known as Parkinson-plus syndrome, are a group of neurodegenerative diseases that include progressive supranuclear palsy (PSP) and multiple system atrophy (MSA). In the early stages, overlapping clinical fea... read more 
Computer Vision and Pattern Recognition

LocateEdit-Bench: A Benchmark for Instruction-Based Editing Localization

arXiv Feb 5, 2026
Recent advancements in image editing have enabled highly controllable and semantically-aware alteration of visual content, posing unprecedented challenges to manipulation localization. However, existing AI-generated forgery localization methods prima... read more 
Computer Vision and Pattern Recognition

LoGoSeg: Integrating Local and Global Features for Open-Vocabulary Semantic Segmentation

arXiv Feb 5, 2026
Open-vocabulary semantic segmentation (OVSS) extends traditional closed-set segmentation by enabling pixel-wise annotation for both seen and unseen categories using arbitrary textual descriptions. While existing methods leverage vision-language model... read more 
Computer Vision and Pattern Recognition

Geometric Observability Index: An Operator-Theoretic Framework for Per-Feature Sensitivity, Weak Observability, and Dynamic Effects in SE(3) Pose Estimation

arXiv Feb 5, 2026
We present a unified operator-theoretic framework for analyzing per-feature sensitivity in camera pose estimation on the Lie group SE(3). Classical sensitivity tools - conditioning analyses, Euclidean perturbation arguments, and Fisher information bo... read more 
Computer Vision and Pattern Recognition

A Mixed Reality System for Robust Manikin Localization in Childbirth Training

arXiv Feb 5, 2026
Opportunities for medical students to gain practical experience in vaginal births are increasingly constrained by shortened clinical rotations, patient reluctance, and the unpredictable nature of labour. To alleviate clinicians' instructional burden ... read more 
Computer Vision and Pattern Recognition cs.ET cs.GR

CAViT -- Channel-Aware Vision Transformer for Dynamic Feature Fusion

arXiv Feb 5, 2026
Vision Transformers (ViTs) have demonstrated strong performance across a range of computer vision tasks by modeling long-range spatial interactions via self-attention. However, channel-wise mixing in ViTs remains static, relying on fixed multilayer p... read more 
Computer Vision and Pattern Recognition cs.AI

Empowering Time Series Analysis with Large-Scale Multimodal Pretraining

arXiv Feb 5, 2026
While existing time series foundation models primarily rely on large-scale unimodal pretraining, they lack complementary modalities to enhance time series understanding. Building multimodal foundation models is a natural next step, but it faces key c... read more 
Machine Learning
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