Identity-aware face completion for face editing applications얼굴 보정 어플리케이션을 위한 고유성 보존 인페인팅

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 67
  • Download : 0
Existing image inpainting methods do not utilize identity information for face completion, producing images of different identities. Considering that identity preservation is important in many real-world face editing applications, we propose a task-specific approach for identity-aware face completion, which is guided by a single reference image containing identity information. Experimental results show that our approach improves the visual quality of the completion results while preserving identity.
Advisors
Kim, Junmoresearcher김준모researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2021
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2021.2,[iii, 15 p. :]

Keywords

face completion▼aimage inpainting▼agenerative adversarial network▼acomputer vision▼adeep learning; 얼굴 인페인팅▼a영상 인페인팅▼a생성적 적대 신경망▼a컴퓨터 비전▼a심층 학습

URI
http://hdl.handle.net/10203/295957
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=948993&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0