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researcher

Ning Yu

23 papers hereh-index 232.8k citations38 works total

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

author position
  • first author7
  • middle author15
  • last author1

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • cs.CV14
  • cs.CR7
  • cs.LG2
same name
  • Ning Yu — 10 papers, h 4
  • Ning Yu — 6 papers, h 1
  • Ning Yu — 6 papers, h 11
  • Ning Yu — 5 papers, h 3
  • Ning Yu — 5 papers, h 4
  • Ning Yu — 4 papers, h 2

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
20162023
most citedGAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models

300 citations · 451 across the 21 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CR2023

Generated Graph Detection

Yihan Ma, Zhikun Zhang, Ning Yu +4

Graph generative models become increasingly effective for data distribution approximation and data augmentation. While they have aroused public concerns about their malicious misus…

cs.CV2023

Detecting Adversarial Faces Using Only Real Face Self-Perturbations

Qian Wang, Yongqin Xian, Hefei Ling +5

Adversarial attacks aim to disturb the functionality of a target system by adding specific noise to the input samples, bringing potential threats to security and robustness when ap…

cs.CV2023★ 4 cited

RoSteALS: Robust Steganography using Autoencoder Latent Space

Tu Bui, Shruti Agarwal, Ning Yu +1

Data hiding such as steganography and invisible watermarking has important applications in copyright protection, privacy-preserved communication and content provenance. Existing wo…

cs.CV2023★ 3 cited

GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation

Can Qin, Ning Yu, Chen Xing +6

Text-to-image (T2I) models based on diffusion processes have achieved remarkable success in controllable image generation using user-provided captions. However, the tight coupling…

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