Importance Annotation for VIP and UIUC Pascal Sentence Datasets
The experimental results for the paper Assigning Relative Importance to Scene Elements in SIBGRAPI’2017 (link to the research page) were obtained using two datasets: VIP dataset and UIUC Pascal Sentence. Both datasets are associated to importance assignment researches and present a wide range of images containing multiple objects per image.
To use both datasets on the paper Assigning Relative Importance to Scene Elements, it was necessary to generate importance annotations, since they are not provided along with dataset images. In addition, the VIP dataset does not provide element (people) bounding boxes and so, it was necessary to annotate these elements before using this dataset. VIP boxes annotations are available in: vip_boxes. To allow the reproduction of the experiments, we also provide the boxes of the UIUC Pascal sentence dataset, available in: uiuc_boxes.
After that, users were asked to generate importance annotations for images of the VIP, UIUC and Pascal Sentence Databases. These annotations are available in: Importance Annotations
You should cite the following paper if you use this dataset in your work.
Motion-Based Representations for Activity Recognition PhD Thesis
Universidade Federal of Minas Gerais, 2020.
Object-based Temporal Segment Relational Network for Activity Recognition Inproceedings
In: Conference on Graphic, Patterns and Images (SIBGRAPI), pp. 1-8, 2018.
In: VISAPP 2018 - International Conference on Computer Vision Theory and Applications, pp. 1-8, 2018.
In: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017.
In: Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 1-8, 2017.
In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016.