26 citations · 73 across the 12 of their papers we have counts for
14 papers
EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks
Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco +6
Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to sta…
Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos
Liao Wang, Qiang Hu, Qihan He +5
The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that util…
HumanGen: Generating Human Radiance Fields with Explicit Priors
Suyi Jiang, Haoran Jiang, Ziyu Wang +3
Recent years have witnessed the tremendous progress of 3D GANs for generating view-consistent radiance fields with photo-realism. Yet, high-quality generation of human radiance fie…
Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objects
Ziyu Wang, Yu Deng, Jiaolong Yang +2
3D-aware generative models have demonstrated their superb performance to generate 3D neural radiance fields (NeRF) from a collection of monocular 2D images even for topology-varyin…
Accelerated chemical space search using a quantum-inspired cluster expansion approach
Hitarth Choubisa, Jehad Abed, Douglas Mendoza +5
To enable the accelerated discovery of materials with desirable properties, it is critical to develop accurate and efficient search algorithms. Quantum annealers and similar quantu…
Cross-lingual Text Classification with Heterogeneous Graph Neural Network
Ziyun Wang, Xuan Liu, Peiji Yang +2
Cross-lingual text classification aims at training a classifier on the source language and transferring the knowledge to target languages, which is very useful for low-resource lan…
MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging
Ziyu Wang, Liao Wang, Fuqiang Zhao +3
Photo-realistic neural reconstruction and rendering of the human portrait are critical for numerous VR/AR applications. Still, existing solutions inherently rely on multi-view capt…
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning
Jinwook Huh, Galen Xing, Ziyun Wang +2
Traditional motion planning is computationally burdensome for practical robots, involving extensive collision checking and considerable iterative propagation of cost values. We pre…
Geodesic-HOF: 3D Reconstruction Without Cutting Corners
Ziyun Wang, Eric A. Mitchell, Volkan Isler +1
Single-view 3D object reconstruction is a challenging fundamental problem in computer vision, largely due to the morphological diversity of objects in the natural world. In particu…
EventGAN: Leveraging Large Scale Image Datasets for Event Cameras
Alex Zihao Zhu, Ziyun Wang, Kaung Khant +1
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, t…
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks
Ziyun Wang, Volkan Isler, Daniel D. Lee
We address the problem of generating a high-resolution surface reconstruction from a single image. Our approach is to learn a Higher Order Function (HOF) which takes an image of an…
Motion Equivariance OF Event-based Camera Data with the Temporal Normalization Transform
Ziyun Wang
In this work, we focus on using convolution neural networks (CNN) to perform object recognition on the event data. In object recognition, it is important for a neural network to be…
Modeling question asking using neural program generation
Ziyun Wang, Brenden M. Lake
People ask questions that are far richer, more informative, and more creative than current AI systems. We propose a neuro-symbolic framework for modeling human question asking, whi…
Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection
Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis +1
Modeling hypernymy, such as poodle is-a dog, is an important generalization aid to many NLP tasks, such as entailment, coreference, relation extraction, and question answering. Sup…