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Yong Rui

4 papers here

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

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0000-0002-9142-5914
same name
  • Yong Rui — 5 papers, h 70
  • Yong Rui — 2 papers, h 6
  • Yong Rui — 2 papers
  • Yong Rui — 1 paper

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
20142024
most citedVisualizing and Comparing Convolutional Neural Networks

52 citations · 53 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024★ 1 cited

Structure Matters: Tackling the Semantic Discrepancy in Diffusion Models for Image Inpainting

Haipeng Liu, Yang Wang, Biao Qian +2

Denoising diffusion probabilistic models for image inpainting aim to add the noise to the texture of image during the forward process and recover masked regions with unmasked ones…

cs.CV2024

DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization

Feng Hou, Jin Yuan, Ying Yang +7

Traditional cross-domain tasks, including domain adaptation and domain generalization, rely heavily on training model by source domain data. With the recent advance of vision-langu…

cs.CV2023

Learning cross space mapping via DNN using large scale click-through logs

Wei Yu, Kuiyuan Yang, Yalong Bai +2

The gap between low-level visual signals and high-level semantics has been progressively bridged by continuous development of deep neural network (DNN). With recent progress of DNN…

cs.CV2014★ 52 cited

Visualizing and Comparing Convolutional Neural Networks

Wei Yu, Kuiyuan Yang, Yalong Bai +2

Convolutional Neural Networks (CNNs) have achieved comparable error rates to well-trained human on ILSVRC2014 image classification task. To achieve better performance, the complexi…

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