Výsledky vyhledávání - "González Franco A"

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EmBARDiment: an Embodied AI Agent for Productivity in XR

Autor: Bovo, Riccardo, Abreu, Steven, Ahuja, Karan, Gonzalez, Eric J, Cheng, Li-Te, Gonzalez-Franco, Mar

XR devices running chat-bots powered by Large Language Models (LLMs) have tremendous potential as always-on agents that can enable much better productivity scenarios. However, screen based chat-bots do not take advantage of the the full-suite of natu

Externí odkaz: http://arxiv.org/abs/2408.08158

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Geometry Fidelity for Spherical Images

Autor: Christensen, Anders, Mojab, Nooshin, Patel, Khushman, Ahuja, Karan, Akata, Zeynep, Winther, Ole, Gonzalez-Franco, Mar, Colaco, Andrea

Spherical or omni-directional images offer an immersive visual format appealing to a wide range of computer vision applications. However, geometric properties of spherical images pose a major challenge for models and metrics designed for ordinary 2D

Externí odkaz: http://arxiv.org/abs/2407.18207

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PARSE-Ego4D: Personal Action Recommendation Suggestions for Egocentric Videos

Autor: Abreu, Steven, Do, Tiffany D., Ahuja, Karan, Gonzalez, Eric J., Payne, Lee, McDuff, Daniel, Gonzalez-Franco, Mar

Intelligent assistance involves not only understanding but also action. Existing ego-centric video datasets contain rich annotations of the videos, but not of actions that an intelligent assistant could perform in the moment. To address this gap, we

Externí odkaz: http://arxiv.org/abs/2407.09503

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Hovering Over the Key to Text Input in XR

Autor: Gonzalez-Franco, Mar, Abdlkarim, Diar, Bhatia, Arpit, Macgregor, Stuart, Fotso-Puepi, Jason Alexander, Gonzalez, Eric J, Seifi, Hasti, Di Luca, Massimiliano, Ahuja, Karan

Virtual, Mixed, and Augmented Reality (XR) technologies hold immense potential for transforming productivity beyond PC. Therefore there is a critical need for improved text input solutions for XR. However, achieving efficient text input in these envi

Externí odkaz: http://arxiv.org/abs/2406.09579

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Augmented Object Intelligence with XR-Objects

Autor: Dogan, Mustafa Doga, Gonzalez, Eric J., Ahuja, Karan, Du, Ruofei, Colaço, Andrea, Lee, Johnny, Gonzalez-Franco, Mar, Kim, David

Seamless integration of physical objects as interactive digital entities remains a challenge for spatial computing. This paper explores Artificial Object Intelligence (AOI) in the context of XR, an interaction paradigm that aims to blur the lines bet

Externí odkaz: http://arxiv.org/abs/2404.13274

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VALID: A perceptually validated Virtual Avatar Library for Inclusion and Diversity

Autor: Do, Tiffany D., Zelenty, Steve, Gonzalez-Franco, Mar, McMahan, Ryan P.

Publikováno v: Frontiers in Virtual Reality 4 (2023)

As consumer adoption of immersive technologies grows, virtual avatars will play a prominent role in the future of social computing. However, as people begin to interact more frequently through virtual avatars, it is important to ensure that the resea

Externí odkaz: http://arxiv.org/abs/2309.10902

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Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Autor: Tian, Junjiao, Aggarwal, Lavisha, Colaco, Andrea, Kira, Zsolt, Gonzalez-Franco, Mar

Publikováno v: Conference on Computer Vision and Pattern Recognition, 2024

Producing quality segmentation masks for images is a fundamental problem in computer vision. Recent research has explored large-scale supervised training to enable zero-shot segmentation on virtually any image style and unsupervised training to enabl

Externí odkaz: http://arxiv.org/abs/2308.12469

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