4 datasets found

The NYUD-v2 dataset is a benchmark for indoor scene segmentation and depth estimation. It contains 1449 images with 4 tasks: semantic segmentation, depth estimation, surface...

The dataset used in this paper for multi-sensor next-best-view planning as matroid-constrained submodular maximization.

The dataset is used for indoor scene understanding and contains RGB and depth images.

Multi-task learning (MTL) research is broadly divided into two categories: one is to learn the correlation between tasks through model structures, and the other is to balance...