5 papers
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
Boxer: Robust Lifting of Open-World 2D Bounding Boxes to 3D
Daniel DeTone, Tianwei Shen, Fan Zhang +4
Detecting and localizing objects in space is a fundamental computer vision problem. While much progress has been made to solve 2D object detection, 3D object localization is much l…
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…
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…
EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models
Julian Straub, Daniel DeTone, Tianwei Shen +3
The advent of wearable computers enables a new source of context for AI that is embedded in egocentric sensor data. This new egocentric data comes equipped with fine-grained 3D loc…