most citedSparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

19 citations · 19 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2017

On the Integration of Optical Flow and Action Recognition

Laura Sevilla-Lara, Yiyi Liao, Fatma Guney +3

Most of the top performing action recognition methods use optical flow as a "black box" input. Here we take a deeper look at the combination of flow and action recognition, and inv…

cs.CV2017

On human motion prediction using recurrent neural networks

Julieta Martinez, Michael J. Black, Javier Romero

Human motion modelling is a classical problem at the intersection of graphics and computer vision, with applications spanning human-computer interaction, motion synthesis, and moti…

cs.CV2017

Optical Flow in Mostly Rigid Scenes

Jonas Wulff, Laura Sevilla-Lara, Michael J. Black

The optical flow of natural scenes is a combination of the motion of the observer and the independent motion of objects. Existing algorithms typically focus on either recovering mo…

cs.CV201719 cited

Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

Timo von Marcard, Bodo Rosenhahn, Michael J. Black +1

We address the problem of making human motion capture in the wild more practical by using a small set of inertial sensors attached to the body. Since the problem is heavily under-c…

cs.CV2016

Optical Flow with Semantic Segmentation and Localized Layers

Laura Sevilla-Lara, Deqing Sun, Varun Jampani +1

Existing optical flow methods make generic, spatially homogeneous, assumptions about the spatial structure of the flow. In reality, optical flow varies across an image depending on…