18 citations · 76 across the 8 of their papers we have counts for
8 papers
A Tutorial on VAEs: From Bayes' Rule to Lossless Compression
Ronald Yu
The Variational Auto-Encoder (VAE) is a simple, efficient, and popular deep maximum likelihood model. Though usage of VAEs is widespread, the derivation of the VAE is not as widely…
Adversarial shape perturbations on 3D point clouds
Daniel Liu, Ronald Yu, Hao Su
The importance of training robust neural network grows as 3D data is increasingly utilized in deep learning for vision tasks in robotics, drone control, and autonomous driving. One…
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers
Daniel Liu, Ronald Yu, Hao Su
3D object classification and segmentation using deep neural networks has been extremely successful. As the problem of identifying 3D objects has many safety-critical applications,…
Adversarial Defense by Stratified Convolutional Sparse Coding
Bo Sun, Nian-hsuan Tsai, Fangchen Liu +2
We propose an adversarial defense method that achieves state-of-the-art performance among attack-agnostic adversarial defense methods while also maintaining robustness to input res…
Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions
Minhyuk Sung, Hao Su, Ronald Yu +1
Various 3D semantic attributes such as segmentation masks, geometric features, keypoints, and materials can be encoded as per-point probe functions on 3D geometries. Given a collec…
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang +1
We introduce Similarity Group Proposal Network (SGPN), a simple and intuitive deep learning framework for 3D object instance segmentation on point clouds. SGPN uses a single networ…
Learning Dense Facial Correspondences in Unconstrained Images
Ronald Yu, Shunsuke Saito, Haoxiang Li +2
We present a minimalistic but effective neural network that computes dense facial correspondences in highly unconstrained RGB images. Our network learns a per-pixel flow and a matc…
Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks
Samuli Laine, Tero Karras, Timo Aila +5
We present a real-time deep learning framework for video-based facial performance capture -- the dense 3D tracking of an actor's face given a monocular video. Our pipeline begins w…