150 citations · 189 across the 4 of their papers we have counts for
4 papers
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
Gedas Bertasius, Christoph Feichtenhofer, Du Tran +2
Modern approaches for multi-person pose estimation in video require large amounts of dense annotations. However, labeling every frame in a video is costly and labor intensive. To r…
Modeling Human Motion with Quaternion-based Neural Networks
Dario Pavllo, Christoph Feichtenhofer, Michael Auli +1
Previous work on predicting or generating 3D human pose sequences regresses either joint rotations or joint positions. The former strategy is prone to error accumulation along the…
Learning Discriminative Motion Features Through Detection
Gedas Bertasius, Christoph Feichtenhofer, Du Tran +2
Despite huge success in the image domain, modern detection models such as Faster R-CNN have not been used nearly as much for video analysis. This is arguably due to the fact that d…
3D human pose estimation in video with temporal convolutions and semi-supervised training
Dario Pavllo, Christoph Feichtenhofer, David Grangier +1
In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully convolutional model based on dilated temporal convolutions over 2D keypoints. We also…