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Guangcong Wang

23 papers hereh-index 171.7k citations29 works total

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

author position
  • first author7
  • middle author15
  • last author1

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • cs.CV20
  • cs.LG3
same name
  • Guangcong Wang — 4 papers, h 1
  • Guangcong Wang — 4 papers, h 3
  • Guangcong Wang — 2 papers, h 3

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
20182026
most citedSceneDreamer: Unbounded 3D Scene Generation from 2D Image Collections

43 citations · 134 across the 22 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023

PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation

Zhaoxi Chen, Fangzhou Hong, Haiyi Mei +3

We present PrimDiffusion, the first diffusion-based framework for 3D human generation. Devising diffusion models for 3D human generation is difficult due to the intensive computati…

cs.CV2023★ 4 cited

PERF: Panoramic Neural Radiance Field from a Single Panorama

Guangcong Wang, Peng Wang, Zhaoxi Chen +3

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single im…

cs.CV2023★ 11 cited

SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesis

Guangcong Wang, Zhaoxi Chen, Chen Change Loy +1

Neural Radiance Field (NeRF) significantly degrades when only a limited number of views are available. To complement the lack of 3D information, depth-based models, such as DSNeRF…

cs.CV2023★ 43 cited

SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collections

Zhaoxi Chen, Guangcong Wang, Ziwei Liu

In this work, we present SceneDreamer, an unconditional generative model for unbounded 3D scenes, which synthesizes large-scale 3D landscapes from random noise. Our framework is le…

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