Search Results for author: Ronald Yu

Found 9 papers, 7 papers with code

A Tutorial on VAEs: From Bayes' Rule to Lossless Compression

1 code implementation18 Jun 2020 Ronald Yu

The Variational Auto-Encoder (VAE) is a simple, efficient, and popular deep maximum likelihood model.


Adversarial shape perturbations on 3D point clouds

2 code implementations16 Aug 2019 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.

3D Point Cloud Classification Autonomous Driving +1

Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

1 code implementation10 Jan 2019 Daniel Liu, Ronald Yu, Hao Su

We present a preliminary evaluation of adversarial attacks on deep 3D point cloud classifiers, namely PointNet and PointNet++, by evaluating both white-box and black-box adversarial attacks that were proposed for 2D images and extending those attacks to reduce the perceptibility of the perturbations in 3D space.

3D Object Classification General Classification +1

Adversarial Defense by Stratified Convolutional Sparse Coding

1 code implementation CVPR 2019 Bo Sun, Nian-hsuan Tsai, Fangchen Liu, Ronald Yu, Hao Su

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 resolution, scale of adversarial perturbation, and scale of dataset size.

Adversarial Defense

Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions

1 code implementation NeurIPS 2018 Minhyuk Sung, Hao Su, Ronald Yu, Leonidas Guibas

Even though our shapes have independent discretizations and no functional correspondences are provided, the network is able to generate latent bases, in a consistent order, that reflect the shared semantic structure among the shapes.


SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

1 code implementation CVPR 2018 Weiyue Wang, Ronald Yu, Qiangui Huang, Ulrich Neumann

Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results.

3D Instance Segmentation 3D Object Detection +5

Realistic Dynamic Facial Textures From a Single Image Using GANs

no code implementations ICCV 2017 Kyle Olszewski, Zimo Li, Chao Yang, Yi Zhou, Ronald Yu, Zeng Huang, Sitao Xiang, Shunsuke Saito, Pushmeet Kohli, Hao Li

By retargeting the PCA expression geometry from the source, as well as using the newly inferred texture, we can both animate the face and perform video face replacement on the source video using the target appearance.

Learning Dense Facial Correspondences in Unconstrained Images

no code implementations ICCV 2017 Ronald Yu, Shunsuke Saito, Haoxiang Li, Duygu Ceylan, Hao Li

To train such a network, we generate a massive dataset of synthetic faces with dense labels using renderings of a morphable face model with variations in pose, expressions, lighting, and occlusions.

Face Alignment Face Model

Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks

1 code implementation21 Sep 2016 Samuli Laine, Tero Karras, Timo Aila, Antti Herva, Shunsuke Saito, Ronald Yu, Hao Li, Jaakko Lehtinen

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.

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