261 citations · 885 across the 23 of their papers we have counts for
5 papers · 1 filter
Learning Deformable Tetrahedral Meshes for 3D Reconstruction
Jun Gao, Wenzheng Chen, Tommy Xiang +4
3D shape representations that accommodate learning-based 3D reconstruction are an open problem in machine learning and computer graphics. Previous work on neural 3D reconstruction…
Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling +4
Differentiable rendering has paved the way to training neural networks to perform "inverse graphics" tasks such as predicting 3D geometry from monocular photographs. To train high…
ScribbleBox: Interactive Annotation Framework for Video Object Segmentation
Bowen Chen, Huan Ling, Xiaohui Zeng +3
Manually labeling video datasets for segmentation tasks is extremely time consuming. In this paper, we introduce ScribbleBox, a novel interactive framework for annotating object in…
Interactive Annotation of 3D Object Geometry using 2D Scribbles
Tianchang Shen, Jun Gao, Amlan Kar +1
Inferring detailed 3D geometry of the scene is crucial for robotics applications, simulation, and 3D content creation. However, such information is hard to obtain, and thus very fe…
Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid
Jun Gao, Zian Wang, Jinchen Xuan +1
In modern computer vision, images are typically represented as a fixed uniform grid with some stride and processed via a deep convolutional neural network. We argue that deforming…