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20212026
most citedAmbient Intelligence for Next-Generation AR

3 citations · 5 across the 26 of their papers we have counts for

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Showing 2026Show all

12 papers · 1 filter

cs.CV2026

Harnessing Vision-Language Models for Perceptual Quality Assessment and Autonomous Content Adjustment in Augmented Reality

Elias Rotondo, Lin Duan, Yanming Xiu +3

Advancements in augmented reality (AR) continue to foster innovative solutions, facilitating novel methodologies within educational systems, healthcare delivery, and risk-mitigatio…

cs.HC2026

Better Situational Awareness in AR-HRC? A Comparative Study of Augmented Reality and Mobile Interfaces for Human-Robot Collaboration

Zhehan Qu, Christian Fronk, Jaewoong Jeong +2

Augmented reality (AR) facilitates human-robot collaboration (HRC) by enabling in-situ spatial visualizations of the robot and the joint task. However, in safety-critical HRC scena…

cs.CV2026

FlexSplat: Flexible Feed-Forward 3D Gaussian Splatting without Point Cloud Correspondence

Amir Sabbaghziarani, Hanting Ye, Maria Gorlatova +1

We present FlexSplat, a feed-forward framework for novel view synthesis (NVS) from uncalibrated, object-centric multi-view image collections. A recent line of query-based methods r…

cs.CV2026

Real-Time Visual Obstruction Detection in Surgical Augmented Reality

Shih-Chin Yang, Yanming Xiu, Hanting Ye +3

Surgical augmented reality (AR) can provide contextual guidance by overlaying virtual annotations, tool cues, and procedural information onto the surgical workspace. However, the v…

cs.HC2026

SHARE: Towards Head-Mounted AR with User-Centric SLAM in Shared Human-Robot Workspaces

Tianyuan Du, Tianyi Hu, Hanting Ye +1

Human-Robot Collaboration (HRC) in shared physical spaces using Augmented Reality (AR) interfaces is powered by Simultaneous Localization and Mapping (SLAM). Existing multi-agent S…

cs.HC2026

ARTOO-DARTU: Studying AR-HRC With AR Obstruction Mitigation During a Warehouse Task

Christian Fronk, Hanting Ye, Zhehan Qu +1

Human-robot collaboration (HRC) often requires robot intentions and internal states to be conveyed to users for task efficiency and safety. Recently, augmented reality (AR) situate…

cs.RO2026

fARfetch: Enabling Collocated AR-HRC in Large Visually Diverse Environments with VLM-Driven AR Content Adaptation

Christian Fronk, Hanting Ye, David Hunt +2

Augmented Reality (AR) can improve collocated human-robot collaboration by making robot state and intent visible and enabling intuitive control, yet large, visually diverse environ…

cs.HC2026

Is It Real? Exploiting Virtual-Physical Discrimination Vulnerability in Mixed Reality

Xueyang Wang, Xihuan Yao, Yanming Xiu +3

Consumer mixed reality (MR) headsets seamlessly blend virtual content into physical environments with sufficient fidelity that users may be unable to distinguish virtual objects fr…

cs.CV2026

Benchmarking Vision-Language Models under Contradictory Virtual Content Attacks in Augmented Reality

Yanming Xiu, Zhengyuan Jiang, Neil Zhenqiang Gong +1

Augmented reality (AR) has rapidly expanded over the past decade. As AR becomes increasingly integrated into daily life, its security and reliability emerge as critical challenges.…

cs.HC2026

Rhythms of Recovery: Patient-Centered Virtual Reality Exergame for Physical Rehabilitation in the Intensive Care Unit

Sangjun Eom, Tianyi Hu, Wenyi Xu +6

Early mobilization is a structured protocol designed to facilitate motor recovery in intensive care unit (ICU) patients with ICU-acquired weakness. This process is typically implem…

cs.CV2026

User Prompting Strategies and Prompt Enhancement Methods for Open-Set Object Detection in XR Environments

Junfeng Lin, Yanming Xiu, Maria Gorlatova

Open-set object detection (OSOD) localizes objects while identifying and rejecting unknown classes at inference. While recent OSOD models perform well on benchmarks, their behavior…

cs.CL2026

Can a Unimodal Language Agent Provide Preferences to Tune a Multimodal Vision-Language Model?

Sazia Tabasum Mim, Jack Morris, Manish Dhakal +3

To explore a more scalable path for adding multimodal capabilities to existing LLMs, this paper addresses a fundamental question: Can a unimodal LLM, relying solely on text, reason…