19 citations · 19 across the 1 of their papers we have counts for
6 papers
LEAP: Learning Articulated Occupancy of People
Marko Mihajlovic, Yan Zhang, Michael J. Black +1
Substantial progress has been made on modeling rigid 3D objects using deep implicit representations. Yet, extending these methods to learn neural models of human shape is still in…
Perpetual Motion: Generating Unbounded Human Motion
Yan Zhang, Michael J. Black, Siyu Tang
The modeling of human motion using machine learning methods has been widely studied. In essence it is a time-series modeling problem involving predicting how a person will move in…
Generating 3D People in Scenes without People
Yan Zhang, Mohamed Hassan, Heiko Neumann +2
We present a fully automatic system that takes a 3D scene and generates plausible 3D human bodies that are posed naturally in that 3D scene. Given a 3D scene without people, humans…
Frontal Low-rank Random Tensors for Fine-grained Action Segmentation
Yan Zhang, Krikamol Muandet, Qianli Ma +2
Fine-grained action segmentation in long untrimmed videos is an important task for many applications such as surveillance, robotics, and human-computer interaction. To understand s…
An Empirical Study towards Understanding How Deep Convolutional Nets Recognize Falls
Yan Zhang, Heiko Neumann
Detecting unintended falls is essential for ambient intelligence and healthcare of elderly people living alone. In recent years, deep convolutional nets are widely used in human ac…
Local Temporal Bilinear Pooling for Fine-grained Action Parsing
Yan Zhang, Siyu Tang, Krikamol Muandet +2
Fine-grained temporal action parsing is important in many applications, such as daily activity understanding, human motion analysis, surgical robotics and others requiring subtle a…