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Ziwei Xu

National University of Singapore

3 papers hereh-index 8871 citations15 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.AI1
affiliations
  • National University of Singapore
Homepage
same name
  • Ziwei Xu — 7 papers, h 3
  • Ziwei Xu — 3 papers
  • Ziwei Xu — 3 papers, h 5
  • Ziwei Xu — 1 paper
  • Ziwei XU — 1 paper
  • Ziwei Xu — 1 paper, h 27

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
20192021
most citedUnsupervised Motion Representation Learning with Capsule Autoencoders

10 citations · 17 across the 3 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Bridging the Intent Gap: Knowledge-Enhanced Visual Generation

Yi Cheng, Ziwei Xu, Dongyun Lin +5

For visual content generation, discrepancies between user intentions and the generated content have been a longstanding problem. This discrepancy arises from two main factors. Firs…

cs.CV2023

A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023

Yi Cheng, Ziwei Xu, Fen Fang +5

In this technical report, we present our findings from a study conducted on the EPIC-KITCHENS-100 Unsupervised Domain Adaptation task for Action Recognition. Our research focuses o…

cs.CV2021★ 10 cited

Unsupervised Motion Representation Learning with Capsule Autoencoders

Ziwei Xu, Xudong Shen, Yongkang Wong +1

We propose the Motion Capsule Autoencoder (MCAE), which addresses a key challenge in the unsupervised learning of motion representations: transformation invariance. MCAE models mot…

cs.CV2020★ 3 cited

GradMix: Multi-source Transfer across Domains and Tasks

Junnan Li, Ziwei Xu, Yongkang Wong +2

The computer vision community is witnessing an unprecedented rate of new tasks being proposed and addressed, thanks to the deep convolutional networks' capability to find complex m…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.