339 citations · 884 across the 9 of their papers we have counts for
5 papers · 1 filter
Active Learning for Deep Object Detection via Probabilistic Modeling
Jiwoong Choi, Ismail Elezi, Hyuk-Jae Lee +2
Active learning aims to reduce labeling costs by selecting only the most informative samples on a dataset. Few existing works have addressed active learning for object detection. M…
Scalable Active Learning for Object Detection
Elmar Haussmann, Michele Fenzi, Kashyap Chitta +7
Deep Neural Networks trained in a fully supervised fashion are the dominant technology in perception-based autonomous driving systems. While collecting large amounts of unlabeled d…
Causal graph-based video segmentation
Camille Couprie, Clément Farabet, Yann LeCun
Numerous approaches in image processing and computer vision are making use of super-pixels as a pre-processing step. Among the different methods producing such over-segmentation of…
Indoor Semantic Segmentation using depth information
Camille Couprie, Clément Farabet, Laurent Najman +1
This work addresses multi-class segmentation of indoor scenes with RGB-D inputs. While this area of research has gained much attention recently, most works still rely on hand-craft…
Clustering Learning for Robotic Vision
Eugenio Culurciello, Jordan Bates, Aysegul Dundar +2
We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters…