You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

We present structured domain randomization (SDR), a variant of domain randomization
(DR) that takes into account the structure of the scene in order to add context to the …

Invariant risk minimization (IRM) has recently emerged as a promising alternative for domain
generalization. Nevertheless, the loss function is difficult to optimize for nonlinear classifiers …

Human life is populated with articulated objects. A comprehensive understanding of
articulated objects, namely appearance, structure, physics property, and semantics, will …

Deep learning methods typically require vast amounts of training data to reach their full
potential. While some publicly available datasets exists, domain specific data always needs …

Generating textual descriptions of images has been an important topic in computer vision
and natural language processing. A number of techniques based on deep learning have …

Machine learning relies heavily on access to large and well-maintained datasets. In this
article, we focus on Computer Vision and object detection applications to survey past …

In this work, we present a procedure to automatically generate an high-quality training
dataset of cable-like objects for semantic segmentation. The proposed method is explained …

Human life is populated with articulated objects. Current Category-level Articulation Pose
Estimation (CAPE) methods are studied under the single-instance setting with a fixed …

Due to its insensitivity to light intensity and the capability to capture multidimensional
information, polarimetric imaging technology has been proven to have advantages over …