Publications (6)
Deep Residual Shrinkage Networks for EMG-based Gesture Identification
Yueying Ma, Chengbo Wang, Chengenze Jiang +1
This work introduces a method for high-accuracy EMG based gesture identification. A newly developed deep learning method, namely, deep residual shrinkage network is applied to perf…
Symmetry-aware Depth Estimation using Deep Neural Networks
Guilin Liu, Chao Yang, Zimo Li +2
Due to the abundance of 2D product images from the Internet, developing efficient and scalable algorithms to recover the missing depth information is central to many applications.…
SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction
Linyong Gan, Zimo Li, Wenxin Xu +4
Accurate long-horizon vessel trajectory prediction remains challenging due to compounded uncertainty from complex navigation behaviors and environmental factors. Existing methods o…
Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis
Zimo Li, Yi Zhou, Shuangjiu Xiao +3
We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN). Recently, r…
ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas +10
We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categori…
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
Yi Zhou, Chenglei Wu, Zimo Li +5
Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher pre…