E. Maggiori et al., "Can semantic labeling methods generalize to any city? The INRIA aerial image labeling benchmark," in IEEE Int. Symp. on Geoscience and Remote Sensing (IGARSS '17), Fort Worth, United States (2017).Maggiori, E.; Tarabalka, Y.; Charpiat, G.; Alliez, P. Can ...
> the image tiles tendtobe self-similar and with uniformcolorhistograms 所以,提出一个开放的数据集合: Dataset features: Coverage of 810 km² (405 km² for training and 405 km² for testing) Aerial orthorectified color imagery with a spatial resolution of 0.3 m Ground truth data for two ...
In this paper, we propose an aerial image labeling dataset that covers a wide range of urban settlement appearances, from different geographic locations. Moreover, the cities included in the test set are different from those of the training set. We also experiment with convolutional neural ...
Inria Aerial Image Labeling Dataset The Inria Aerial Image Labeling addresses a core topic in remote sensing: the automatic pixelwise labeling of aerial imagery . Dataset features: Coverage of 810 km² (405 km² for training and 405 km² for testing). Aerial orthorectified color imagery wit...
Alliez, “Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark,” in IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. [25] S. Paisitkriangkrai, J. Sherrah, P. Janney, and A. Van Den Hengel, “Semantic labeling ...
Inria Aerial Image Labeling Dataset Link to the dataset:https://project.inria.fr/aerialimagelabeling/ For the Inria dataset, the original ground truth is just a collection of raster masks. As our method requires annotations to be polygons in order to compute the ground truth angle for the fra...
For example, the gCRF and gCRF_MBI methods perform better than MBI_gCRF in the first and second images taken from WHU Building Dataset. However, the two test images from INRIA aerial image dataset obtain different results. Table 3. Quantitative evaluation (%) of different methods with public ...
Semantic segmentation consists of attributing a class to each pixel of an image. This type of segmentation is reasonably well-resolved for building segmentation from very high resolution images. For example, for the Inria Aerial Image Labeling Dataset [3], which is a dataset of buildings for 10...
LabelMe dataset LabelMe is a web-based image annotation tool that allows researchers to label images and share the annotations with the rest of the community. If you use the database, we only ask that you contribute to it, from time to time, by using the labeling tool. BioID Face Detec...
Seeing 3D chairs: exemplar part-based 2D-3D alignment using a large dataset of CAD models (PDF, project) Mathieu Aubry* (INRIA), Daniel Maturana (CMU), Alexei Efros (UC Berkeley), Bryan Russell (Intell), Josef Sivic (INRIA) Fourier Analysis on Transient Imaging with a Multifrequency Time...