activity
20162022
most citedHistory Repeats Itself: Human Motion Prediction via Motion Attention

30 citations · 109 across the 13 of their papers we have counts for

collaborators

18 papers

cs.CV20214 cited

Multi-level Motion Attention for Human Motion Prediction

Wei Mao, Miaomiao Liu, Mathieu Salzmann +1

Human motion prediction aims to forecast future human poses given a historical motion. Whether based on recurrent or feed-forward neural networks, existing learning based methods f…

eess.IV202122 cited

Dense Reconstruction of Transparent Objects by Altering Incident Light Paths Through Refraction

Kai Han, Kwan-Yee K. Wong, Miaomiao Liu

This paper addresses the problem of reconstructing the surface shape of transparent objects. The difficulty of this problem originates from the viewpoint dependent appearance of a…

cs.CV20214 cited

Self-supervised Learning of Depth Inference for Multi-view Stereo

Jiayu Yang, Jose M. Alvarez, Miaomiao Liu

Recent supervised multi-view depth estimation networks have achieved promising results. Similar to all supervised approaches, these networks require ground-truth data during traini…

cs.CV20213 cited

Fixed Viewpoint Mirror Surface Reconstruction under an Uncalibrated Camera

Kai Han, Miaomiao Liu, Dirk Schnieders +1

This paper addresses the problem of mirror surface reconstruction, and proposes a solution based on observing the reflections of a moving reference plane on the mirror surface. Unl…

cs.CV20204 cited

Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration

Liyuan Pan, Shah Chowdhury, Richard Hartley +3

The dual-pixel (DP) hardware works by splitting each pixel in half and creating an image pair in a single snapshot. Several works estimate depth/inverse depth by treating the DP pa…

cs.CV202030 cited

History Repeats Itself: Human Motion Prediction via Motion Attention

Wei Mao, Miaomiao Liu, Mathieu Salzmann

Human motion prediction aims to forecast future human poses given a past motion. Whether based on recurrent or feed-forward neural networks, existing methods fail to model the obse…