DIFFER: Moving Beyond 3D Reconstruction with Differentiable Feature Rendering

Navaneet K. L., Priyanka Mandikal, Varun Jampani, R. Venkatesh Babu
2019 Computer Vision and Pattern Recognition  
Perception of 3D object properties from 2D images form one of the core computer vision problems. In this work, we propose a deep learning system that can simultaneously reason about 3D shape as well as associated properties (such as color, semantic part segments) directly from a single 2D image. We devise a novel depth-aware differentiable feature rendering module (DIFFER) that is used to train our model by using only 2D supervision. Experiments on both synthetic ShapeNet dataset and the
more » ... rld Pix3D dataset demonstrate that our 2D supervised DIFFER model performs on par or sometimes even outperforms existing 3D supervised models.
dblp:conf/cvpr/LMJB19 fatcat:djms5h3eavfcpk4qamxfr2le34