Publication: IEEE International Conference on Robotics and Automation (ICRA)
Abstract: The state of the art in computer vision has rapidly advanced over the past decade largely aided by shared image datasets. However, most of these datasets tend to consist of assorted collections of images from the web that do not include 3D information or pose information. Furthermore, they target the problem of object category recognition—whereas solving the problem of object instance recognition might be sufficient for many robotic tasks. To address these issues, we present a highquality, large-scale dataset of 3D object instances, with accurate calibration information for every image. We anticipate that “solving” this dataset will effectively remove many perceptionrelated problems for mobile, sensing-based robots.
Bibtex:
@inproceedings{singh_bigbird_2014, title = {{BigBIRD}: {A} large-scale {3D} database of object instances}, isbn = {978-1-4799-3685-4}, shorttitle = {{BigBIRD}}, doi = {10.1109/ICRA.2014.6906903}, urldate = {2021-07-13}, booktitle = {{IEEE} {International} {Conference} on {Robotics} and {Automation} ({ICRA})}, author = {Singh, Arjun and Sha, James and Narayan, Karthik S. and Achim, Tudor and Abbeel, Pieter}, year = {2014}, pages = {509--516}, file = {2014-ICRA-BigBIRD.pdf:C\:\\Users\\Luigi\\Zotero\\storage\\59NTZTAA\\2014-ICRA-BigBIRD.pdf:application/pdf} }