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Mingming Gong

68 papers hereh-index 449.6k citations128 works total

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

author position
  • first author2
  • middle author62
  • last author1

Across the 65 of 68 papers where every author was matched, so the position is known.

fields
  • cs.LG32
  • cs.CV24
  • stat.ML8
  • cs.AI1
  • cs.IR1
  • eess.IV1
same name
  • Mingming Gong — 31 papers, h 10
  • Mingming Gong — 16 papers, h 8
  • Mingming Gong — 10 papers, h 5
  • Mingming Gong — 7 papers, h 8
  • Mingming Gong — 7 papers, h 4
  • Mingming Gong — 6 papers, h 4

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
20142026
most citedAdaptive Context-Aware Multi-Modal Network for Depth Completion

175 citations · 1.2k across the 65 of their papers we have counts for

collaborators
Showing 2020 · cs.CVShow all

4 papers · 2 filters

cs.CV2020★ 2 cited

Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning

Huan Fu, Shunming Li, Rongfei Jia +3

Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D shape of a given 2D image from a large 3D shape database. The common routine is to map 2D images and 3D shap…

cs.CV2020★ 16 cited

3D-FUTURE: 3D Furniture shape with TextURE

Huan Fu, Rongfei Jia, Lin Gao +4

The 3D CAD shapes in current 3D benchmarks are mostly collected from online model repositories. Thus, they typically have insufficient geometric details and less informative textur…

cs.CV2020★ 2 cited

Short-Term and Long-Term Context Aggregation Network for Video Inpainting

Ang Li, Shanshan Zhao, Xingjun Ma +5

Video inpainting aims to restore missing regions of a video and has many applications such as video editing and object removal. However, existing methods either suffer from inaccur…

cs.CV2020★ 175 cited

Adaptive Context-Aware Multi-Modal Network for Depth Completion

Shanshan Zhao, Mingming Gong, Huan Fu +1

Depth completion aims to recover a dense depth map from the sparse depth data and the corresponding single RGB image. The observed pixels provide the significant guidance for the r…

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