Learning 3D shape completion under weak supervision; on ShapeNet, ModelNet, KITTI and Kinect data; published at CVPR and on ArXiv.
Weakly-supervised shape completion of cars on KITTI using variational auto-encoders; including two synthetic ShapeNet-based benchmark datasets.
Revised C++ implementations of two popular superpixel algorithms, SEEDS and FH, which are shown to outperform the original implementations.
A comprehensive comparison and evaluation of 28 superpixel algorithms on 5 different datasets; published in CVIU and GCPR.
Efficient C++ implementation for hierarchical graph-based image segmentation.
Efficient C++ implementation of iPiano, a proximal algorithm with inertial force for non-convex and non-smooth optimization; including applications to image segmentation.
A comparison of several state-of-the-art superpixel algorithms using an extended version of the Berkeley Segmentation Benchmark.