Computer Vision

Visual perception can be used by robotic leg prostheses and exoskeletons to improve the accuracy and speed of transitions between different locomotion mode controllers (e.g., level-ground walking to stair ascent) by sensing the walking environment prior to physical interactions. Here we developed the StairNet dataset to support the development of vision-based stair recognition systems.


One of the weak points of most of denoising algoritms (deep learning based ones) is the training data. Due to no or very limited amount of groundtruth data available, these algorithms are often evaluated using synthetic noise models such as Additive Zero-Mean Gaussian noise. The downside of this approach is that these simple model do not represent noise present in natural imagery.


Retail Gaze, a dataset for remote gaze estimation in real-world retail environments. Retail Gaze is composed of 3,922 images of individuals looking at products in a retail environment, with 12 camera capture angles.

Each image captures the third-person view of the customer and shelves. Location of the gaze point, the Bounding box of the person's head, segmentation masks of the gazed at product areas are provided as annotations.


A dataset with more comprehensive category labels, richer data scenes, and more diverse image sizes were constructed. All images had been labeled.
The num of all annotations is 8232. This dataset is openly accessible to all future research workers for rapid deployment of mask detection subtasks during the New Crown out- break and in all possible future scenarios.


In this paper, we propose a framework for 3D human pose estimation using a single 360° camera mounted on the user's wrist. Perceiving a 3D human pose with such a simple setup has remarkable potential for various applications (e.g., daily-living activity monitoring, motion analysis for sports training). However, no existing method has tackled this task due to the difficulty of estimating a human pose from a single camera image in which only a part of the human body is captured, and because of a lack of training data.


Document layout analysis (DLA) plays an important role for identifying and classifying the different regions of digital documents in the context of Document Understanding tasks. In light of this, SciBank seeks to provide a considerable amount  of data from text (abstract, text blocks, caption, keywords, reference, section, subsection, title), tables, figures and equations (isolated equations and inline equations) of 74435 scientific articles pages. Human curators validated that these 12 regions were properly labeled.


This dataset was prepared to aid in the creation of a machine learning algorithm that would classify the white blood cells in thin blood smears of juvenile Visayan warty pigs. The creation of this dataset was deemed imperative because of the limited availability of blood smear images collected from the critically endangered species on the internet. The dataset contains 3,457 images of various types of white blood cells (JPEG) with accompanying cell type labels (XLSX).


Automated driving in public traffic still faces many technical and legal challenges. However, automating vehicles at low speeds in controlled industrial environments is already achievable today. A reliable obstacle detection is mandatory to prevent accidents. Recent advances in convolutional neural network-based algorithms have made it conceivable to replace distance measuring laser scanners with common monocameras.


The Active-Passive SimStereo dataset is a simulated dataset created with Blender containing high quality both realistic and abstract looking images. Each image pair is rendered in classic RGB domain, as well as Near-Infrared with an active pattern. It is meant to be used as a dataset to study domain transfert between active and passive stereo vision, as well as providing a high quality active stereo dataset, which are far less common than passive stereo datasets.