Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

The goal of this paper is to review the state-of-the-art progress on visual tracking methods,
classify them into different categories, as well as identify future trends. Visual tracking is a …

Random forest is one of the most widely used machine learning algorithms. Decision trees
used to construct the random forest may have low classification accuracies or high …

In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast system for panoptic
segmentation, aiming to establish a solid baseline for bottom-up methods that can achieve …

Current 3D object detection methods are heavily influenced by 2D detectors. In order to
leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids …

This paper introduces VEDAI: Vehicle Detection in Aerial Imagery a new database of aerial
images provided as a tool to benchmark automatic target recognition algorithms in …

The aim of single image super-resolution is to reconstruct a high-resolution image from a
single low-resolution input. Although the task is ill-posed it can be seen as finding a non …

We introduce a novel method for robust and accurate 3D object pose estimation from a
single color image under large occlusions. Following recent approaches, we first predict the …

This paper presents a patch-based approach for crowd density estimation in public scenes.
We formulate the problem of estimating density in a structured learning framework applied to …

The design of complexity-aware cascaded detectors, combining features of very different
complexities, is considered. A new cascade design procedure is introduced, by formulating …