1 citations · 4 across the 6 of their papers we have counts for
6 papers
Floating No More: Object-Ground Reconstruction from a Single Image
Yunze Man, Yichen Sheng, Jianming Zhang +2
Recent advancements in 3D object reconstruction from single images have primarily focused on improving the accuracy of object shapes. Yet, these techniques often fail to accurately…
DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision
Lu Ling, Yichen Sheng, Zhi Tu +17
We have witnessed significant progress in deep learning-based 3D vision, ranging from neural radiance field (NeRF) based 3D representation learning to applications in novel view sy…
Dr.Bokeh: DiffeRentiable Occlusion-aware Bokeh Rendering
Yichen Sheng, Zixun Yu, Lu Ling +6
Bokeh is widely used in photography to draw attention to the subject while effectively isolating distractions in the background. Computational methods simulate bokeh effects withou…
PixHt-Lab: Pixel Height Based Light Effect Generation for Image Compositing
Yichen Sheng, Jianming Zhang, Julien Philip +5
Lighting effects such as shadows or reflections are key in making synthetic images realistic and visually appealing. To generate such effects, traditional computer graphics uses a…
Controllable Shadow Generation Using Pixel Height Maps
Yichen Sheng, Yifan Liu, Jianming Zhang +6
Shadows are essential for realistic image compositing. Physics-based shadow rendering methods require 3D geometries, which are not always available. Deep learning-based shadow synt…
SSN: Soft Shadow Network for Image Compositing
Yichen Sheng, Jianming Zhang, Bedrich Benes
We introduce an interactive Soft Shadow Network (SSN) to generates controllable soft shadows for image compositing. SSN takes a 2D object mask as input and thus is agnostic to imag…