3 citations · 6 across the 3 of their papers we have counts for
9 papers
Flow Guided Transformable Bottleneck Networks for Motion Retargeting
Jian Ren, Menglei Chai, Oliver J. Woodford +2
Human motion retargeting aims to transfer the motion of one person in a "driving" video or set of images to another person. Existing efforts leverage a long training video from eac…
Motion Representations for Articulated Animation
Aliaksandr Siarohin, Oliver J. Woodford, Jian Ren +2
We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tra…
Teachers Do More Than Teach: Compressing Image-to-Image Models
Qing Jin, Jian Ren, Oliver J. Woodford +4
Generative Adversarial Networks (GANs) have achieved huge success in generating high-fidelity images, however, they suffer from low efficiency due to tremendous computational cost…
Progressive Batching for Efficient Non-linear Least Squares
Huu Le, Christopher Zach, Edward Rosten +1
Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements of the basic Gauss-Newton algorithm tackle converg…
Large Scale Photometric Bundle Adjustment
Oliver J. Woodford, Edward Rosten
Direct methods have shown promise on visual odometry and SLAM, leading to greater accuracy and robustness over feature-based methods. However, offline 3-d reconstruction from inter…
Data Augmentation for Graph Neural Networks
Tong Zhao, Yozen Liu, Leonardo Neves +3
Data augmentation has been widely used to improve generalizability of machine learning models. However, comparatively little work studies data augmentation for graphs. This is larg…