23 citations · 44 across the 10 of their papers we have counts for
5 papers · 1 filter
Temporal Convolutional Networks for Action Segmentation and Detection
Colin Lea, Michael D. Flynn, Rene Vidal +2
The ability to identify and temporally segment fine-grained human actions throughout a video is crucial for robotics, surveillance, education, and beyond. Typical approaches decoup…
Temporal Convolutional Networks: A Unified Approach to Action Segmentation
Colin Lea, Rene Vidal, Austin Reiter +1
The dominant paradigm for video-based action segmentation is composed of two steps: first, for each frame, compute low-level features using Dense Trajectories or a Convolutional Ne…
SANTIAGO: Spine Association for Neuron Topology Improvement and Graph Optimization
William Gray Roncal, Colin Lea, Akira Baruah +1
Developing automated and semi-automated solutions for reconstructing wiring diagrams of the brain from electron micrographs is important for advancing the field of connectomics. Wh…
Recognizing Surgical Activities with Recurrent Neural Networks
Robert DiPietro, Colin Lea, Anand Malpani +5
We apply recurrent neural networks to the task of recognizing surgical activities from robot kinematics. Prior work in this area focuses on recognizing short, low-level activities,…
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation
Colin Lea, Austin Reiter, Rene Vidal +1
Joint segmentation and classification of fine-grained actions is important for applications of human-robot interaction, video surveillance, and human skill evaluation. However, des…