2269 results for "earn" across all locations

K. Wong, S. Wang, M. Ren, M. Liang, R. Urtasun
We propose a novel open-set instance segmentation algorithm for point clouds that identifies instances from both known and unknown classes. In particular, we train a deep convolutional neural network that projects points belonging to the same instance together in a category-agnostic embedding space. [PDF]
The Conference on Robot Learning (CoRL), 2019

M. Li, Z. Lin, R. Mech, E. Yumer, D. Ramanan

Edges, boundaries and contours are important subjects of study in both computer graphics and computer vision. On one hand, they are the 2D elements that convey 3D shapes, on the other hand, they are indicative of occlusion events and thus separation of objects or semantic concepts. In this paper, we aim to generate contour drawings, boundary-like drawings that capture the outline of the visual scene. Prior art often cast this problem as boundary detection. […] [PDF]
Winter Conference on Applications of Computer Vision (WACV), 2019

Y. Zhang, L. Gueguen, I. Zharkov, P. Zhang, K. Seifert, B. Kadlec
Optical Character Recognition (OCR) approaches have been widely advanced in recent years thanks to the resurgence of deep learning. The state-of-the-art models are mainly trained on the datasets consisting of the constrained scenes. Detecting and recognizing text from the real-world images remains a technical challenge. […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2017