activity
20222024
most citedDoF-NeRF: Depth-of-Field Meets Neural Radiance Fields

33 citations · 70 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20242 cited

iControl3D: An Interactive System for Controllable 3D Scene Generation

Xingyi Li, Yizheng Wu, Jun Cen +6

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D…

cs.CV2024

Dynamic Neural Radiance Field From Defocused Monocular Video

Xianrui Luo, Huiqiang Sun, Juewen Peng +1

Dynamic Neural Radiance Field (NeRF) from monocular videos has recently been explored for space-time novel view synthesis and achieved excellent results. However, defocus blur caus…

cs.CV202314 cited

Make-It-4D: Synthesizing a Consistent Long-Term Dynamic Scene Video from a Single Image

Liao Shen, Xingyi Li, Huiqiang Sun +4

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camer…

cs.CV202317 cited

Defocus to focus: Photo-realistic bokeh rendering by fusing defocus and radiance priors

Xianrui Luo, Juewen Peng, Ke Xian +2

We consider the problem of realistic bokeh rendering from a single all-in-focus image. Bokeh rendering mimics aesthetic shallow depth-of-field (DoF) in professional photography, bu…

cs.CV20234 cited

Point-and-Shoot All-in-Focus Photo Synthesis from Smartphone Camera Pair

Xianrui Luo, Juewen Peng, Weiyue Zhao +3

All-in-Focus (AIF) photography is expected to be a commercial selling point for modern smartphones. Standard AIF synthesis requires manual, time-consuming operations such as focal…

cs.CV202233 cited

DoF-NeRF: Depth-of-Field Meets Neural Radiance Fields

Zijin Wu, Xingyi Li, Juewen Peng +3

Neural Radiance Field (NeRF) and its variants have exhibited great success on representing 3D scenes and synthesizing photo-realistic novel views. However, they are generally based…