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Yiming Gao

4 papers hereh-index 5711 citations6 works total

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

author position
  • middle author4

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

fields
  • cs.CV4
same name
  • Yiming Gao — 8 papers, h 8
  • Yiming Gao — 5 papers, h 3
  • Yiming Gao — 4 papers, h 1
  • Yiming Gao — 4 papers, h 7
  • Yiming Gao — 3 papers, h 3
  • Yiming Gao — 3 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

most citedInstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

18 citations · 31 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024

NovelGS: Consistent Novel-view Denoising via Large Gaussian Reconstruction Model

Jinpeng Liu, Jiale Xu, Weihao Cheng +4

We introduce NovelGS, a diffusion model for Gaussian Splatting (GS) given sparse-view images. Recent works leverage feed-forward networks to generate pixel-aligned Gaussians, which…

cs.CV2024★ 2 cited

MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions

Xuan Ju, Yiming Gao, Zhaoyang Zhang +6

Sora's high-motion intensity and long consistent videos have significantly impacted the field of video generation, attracting unprecedented attention. However, existing publicly av…

cs.CV2024★ 18 cited

InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Jiale Xu, Weihao Cheng, Yiming Gao +3

We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalabil…

cs.CV2024★ 11 cited

Advances in 3D Generation: A Survey

Xiaoyu Li, Qi Zhang, Di Kang +7

Generating 3D models lies at the core of computer graphics and has been the focus of decades of research. With the emergence of advanced neural representations and generative model…

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