20 citations · 26 across the 12 of their papers we have counts for
14 papers
Beyond Gestures: Estimating Full Hand Pose and Contact Forces from Wrist-Worn Pressure Sensor Array
Svetoslav Kolev, Lingni Ma, Michael Goesele +3
Capturing hand motion and interaction forces is critical for interactive computing, VR, and high-fidelity tactile demonstrations for robot learning. We introduce a wrist-worn press…
LAMP: Localization Aware Multi-camera People Tracking in Metric 3D World
Nan Yang, Julian Straub, Fan Zhang +3
Tracking 3D human motion from egocentric multi-camera headset is challenged by severe egomotion, partial visibility or occlusions and lack of training data. Existing methods design…
Aria Gen 2 Pilot Dataset
Chen Kong, James Fort, Aria Kang +20
The Aria Gen 2 Pilot Dataset (A2PD) is an egocentric multimodal open dataset captured using the state-of-the-art Aria Gen 2 glasses. To facilitate timely access, A2PD is released i…
Benchmarking Egocentric Visual-Inertial SLAM at City Scale
Anusha Krishnan, Shaohui Liu, Paul-Edouard Sarlin +6
Precise 6-DoF simultaneous localization and mapping (SLAM) from onboard sensors is critical for wearable devices capturing egocentric data, which exhibits specific challenges, such…
Photoreal Scene Reconstruction from an Egocentric Device
Zhaoyang Lv, Maurizio Monge, Ka Chen +5
In this paper, we investigate the challenges associated with using egocentric devices to photorealistic reconstruct the scene in high dynamic range. Existing methodologies typicall…
Sonata: Self-Supervised Learning of Reliable Point Representations
Xiaoyang Wu, Daniel DeTone, Duncan Frost +7
In this paper, we question whether we have a reliable self-supervised point cloud model that can be used for diverse 3D tasks via simple linear probing, even with limited data and…
Human-in-the-Loop Local Corrections of 3D Scene Layouts via Infilling
Christopher Xie, Armen Avetisyan, Henry Howard-Jenkins +5
We present a novel human-in-the-loop approach to estimate 3D scene layout that uses human feedback from an egocentric standpoint. We study this approach through introduction of a n…
HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videos
Prithviraj Banerjee, Sindi Shkodrani, Pierre Moulon +11
We introduce HOT3D, a publicly available dataset for egocentric hand and object tracking in 3D. The dataset offers over 833 minutes (3.7M+ images) of recordings that feature 19 sub…
Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking
Prithviraj Banerjee, Sindi Shkodrani, Pierre Moulon +9
We introduce HOT3D, a publicly available dataset for egocentric hand and object tracking in 3D. The dataset offers over 833 minutes (more than 3.7M images) of multi-view RGB/monoch…
Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild
Lingni Ma, Yuting Ye, Fangzhou Hong +14
We introduce Nymeria - a large-scale, diverse, richly annotated human motion dataset collected in the wild with multiple multimodal egocentric devices. The dataset comes with a) fu…
SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model
Armen Avetisyan, Christopher Xie, Henry Howard-Jenkins +11
We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our propose…
Aria Everyday Activities Dataset
Zhaoyang Lv, Nicholas Charron, Pierre Moulon +21
We present Aria Everyday Activities (AEA) Dataset, an egocentric multimodal open dataset recorded using Project Aria glasses. AEA contains 143 daily activity sequences recorded by…
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…
Robust Indoor Localization with Ranging-IMU Fusion
Fan Jiang, David Caruso, Ashutosh Dhekne +3
Indoor wireless ranging localization is a promising approach for low-power and high-accuracy localization of wearable devices. A primary challenge in this domain stems from non-lin…