136 citations · 328 across the 21 of their papers we have counts for
22 papers
Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications
Weiyu Feng, Seth Z. Zhao, Chuanyu Pan +4
Digital twin is a problem of augmenting real objects with their digital counterparts. It can underpin a wide range of applications in augmented reality (AR), autonomy, and UI/UX. A…
Mutual Scene Synthesis for Mixed Reality Telepresence
Mohammad Keshavarzi, Michael Zollhoefer, Allen Y. Yang +2
Remote telepresence via next-generation mixed reality platforms can provide higher levels of immersion for computer-mediated communications, allowing participants to engage in a wi…
Soft Expectation and Deep Maximization for Image Feature Detection
Alexander Mai, Allen Yang, Dominique E. Meyer
Central to the application of many multi-view geometry algorithms is the extraction of matching points between multiple viewpoints, enabling classical tasks such as camera pose est…
Contextual Scene Augmentation and Synthesis via GSACNet
Mohammad Keshavarzi, Flaviano Christian Reyes, Ritika Shrivastava +3
Indoor scene augmentation has become an emerging topic in the field of computer vision and graphics with applications in augmented and virtual reality. However, current state-of-th…
GenScan: A Generative Method for Populating Parametric 3D Scan Datasets
Mohammad Keshavarzi, Oladapo Afolabi, Luisa Caldas +2
The availability of rich 3D datasets corresponding to the geometrical complexity of the built environments is considered an ongoing challenge for 3D deep learning methodologies. To…
SceneGen: Generative Contextual Scene Augmentation using Scene Graph Priors
Mohammad Keshavarzi, Aakash Parikh, Xiyu Zhai +3
Spatial computing experiences are constrained by the real-world surroundings of the user. In such experiences, augmenting virtual objects to existing scenes require a contextual ap…