◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

ZiYun Wang

14 papers hereh-index 344.9k citations159 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author7
  • middle author5

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.CL3
  • cs.RO2
  • physics.comp-ph1
same name
  • Ziyun Wang — 35 papers, h 34
  • Ziyun Wang — 10 papers, h 6
  • Ziyun Wang — 2 papers, h 2
  • Ziyun Wang — 1 paper, h 41
  • Ziyun Wang — 1 paper, h 4
  • Ziyun Wang — 1 paper, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedEV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks

26 citations · 73 across the 12 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

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…

cs.CV2019

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…

cs.CV2019

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…

cs.CL2019★ 11 cited

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…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.