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S. Dong

4 papers hereh-index 181.8k citations100 works total

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

author position
  • first author4

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

fields
  • cs.CV4
same name
  • S. Dong — 114 papers, h 54
  • S. Dong — 95 papers, h 45
  • S. Dong — 36 papers, h 58
  • S. Dong — 24 papers, h 35
  • S. Dong — 19 papers, h 28
  • S. Dong — 17 papers, h 21

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

most citedImplicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization

3 citations · 4 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2023

Weakly Supervised 3D Instance Segmentation without Instance-level Annotations

Shichao Dong, Guosheng Lin

3D semantic scene understanding tasks have achieved great success with the emergence of deep learning, but often require a huge amount of manually annotated training data. To allev…

cs.CV2022★ 3 cited

Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization

Shichao Dong, Jin Wang, Renhe Ji +3

In this paper, we analyse the generalization ability of binary classifiers for the task of deepfake detection. We find that the stumbling block to their generalization is caused by…

cs.CV2022★ 1 cited

Collaborative Propagation on Multiple Instance Graphs for 3D Instance Segmentation with Single-point Supervision

Shichao Dong, Ruibo Li, Jiacheng Wei +2

Instance segmentation on 3D point clouds has been attracting increasing attention due to its wide applications, especially in scene understanding areas. However, most existing meth…

cs.CV2022

Explaining Deepfake Detection by Analysing Image Matching

Shichao Dong, Jin Wang, Jiajun Liang +2

This paper aims to interpret how deepfake detection models learn artifact features of images when just supervised by binary labels. To this end, three hypotheses from the perspecti…

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