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Xiaohui Zeng

12 papers hereh-index 10556 citations14 works total

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

author position
  • middle author9
  • last author1

Across the 10 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.RO2
  • cs.AI1
same name
  • Xiaohui Zeng — 13 papers, h 12
  • Xiaohui Zeng — 5 papers, h 3
  • Xiaohui Zeng — 2 papers, h 2
  • Xiaohui Zeng — 1 paper
  • Xiaohui Zeng — 1 paper, h 2
  • Xiaohui Zeng — 1 paper, 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

activity
20242026
most citedEdify 3D: Scalable High-Quality 3D Asset Generation

3 citations · 8 across the 12 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

4 papers · 2 filters

cs.CV2024★ 3 cited

Edify 3D: Scalable High-Quality 3D Asset Generation

NVIDIA, :, Maciej Bala +22

We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at mul…

cs.CV2024

Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models

NVIDIA, :, Yuval Atzmon +29

We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space dif…

cs.CV2024★ 1 cited

Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos

Jiahe Liu, Youran Qu, Qi Yan +3

Significant advancements have been made in video generative models recently. Unlike image generation, video generation presents greater challenges, requiring not only generating hi…

cs.CV2024

Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation

Yunhao Ge, Xiaohui Zeng, Jacob Samuel Huffman +3

Existing automatic captioning methods for visual content face challenges such as lack of detail, content hallucination, and poor instruction following. In this work, we propose Vis…

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