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Gyeongsik Moon

30 papers hereh-index 244.5k citations41 works total

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

author position
  • sole author2
  • first author12
  • middle author13
  • last author1

Across the 28 of 30 papers where every author was matched, so the position is known.

fields
  • cs.CV29
  • physics.ins-det1
same name
  • Gyeongsik Moon — 5 papers, h 7

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
20172026
most citedHolistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation

15 citations · 42 across the 17 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 1 cited

MultiAct: Long-Term 3D Human Motion Generation from Multiple Action Labels

Taeryung Lee, Gyeongsik Moon, Kyoung Mu Lee

We tackle the problem of generating long-term 3D human motion from multiple action labels. Two main previous approaches, such as action- and motion-conditioned methods, have limita…

cs.CV2022

MonoNHR: Monocular Neural Human Renderer

Hongsuk Choi, Gyeongsik Moon, Matthieu Armando +3

Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas. In…

cs.CV2022★ 1 cited

3D Clothed Human Reconstruction in the Wild

Gyeongsik Moon, Hyeongjin Nam, Takaaki Shiratori +1

Although much progress has been made in 3D clothed human reconstruction, most of the existing methods fail to produce robust results from in-the-wild images, which contain diverse…

cs.CV2022★ 14 cited

HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network

JoonKyu Park, Yeonguk Oh, Gyeongsik Moon +2

Hands are often severely occluded by objects, which makes 3D hand mesh estimation challenging. Previous works often have disregarded information at occluded regions. However, we ar…

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