119 citations · 122 across the 5 of their papers we have counts for
7 papers · 1 filter
Context-Aware Sequence Alignment using 4D Skeletal Augmentation
Taein Kwon, Bugra Tekin, Siyu Tang +1
Temporal alignment of fine-grained human actions in videos is important for numerous applications in computer vision, robotics, and mixed reality. State-of-the-art methods directly…
Reconstructing and grounding narrated instructional videos in 3D
Dimitri Zhukov, Ignacio Rocco, Ivan Laptev +4
Narrated instructional videos often show and describe manipulations of similar objects, e.g., repairing a particular model of a car or laptop. In this work we aim to reconstruct su…
H2O: Two Hands Manipulating Objects for First Person Interaction Recognition
Taein Kwon, Bugra Tekin, Jan Stuhmer +2
We present a comprehensive framework for egocentric interaction recognition using markerless 3D annotations of two hands manipulating objects. To this end, we propose a method to c…
HoloLens 2 Research Mode as a Tool for Computer Vision Research
Dorin Ungureanu, Federica Bogo, Silvano Galliani +9
Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision re…
Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction
Yana Hasson, Bugra Tekin, Federica Bogo +3
Modeling hand-object manipulations is essential for understanding how humans interact with their environment. While of practical importance, estimating the pose of hands and object…
H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions
Bugra Tekin, Federica Bogo, Marc Pollefeys
We present a unified framework for understanding 3D hand and object interactions in raw image sequences from egocentric RGB cameras. Given a single RGB image, our model jointly est…