58 citations · 325 across the 29 of their papers we have counts for
4 papers · 1 filter
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
An activation boundary for a neuron refers to a separating hyperplane that determines whether the neuron is activated or deactivated. It has been long considered in neural networks…
C3: Concentrated-Comprehensive Convolution and its application to semantic segmentation
Hyojin Park, Youngjoon Yoo, Geonseok Seo +3
One of the practical choices for making a lightweight semantic segmentation model is to combine a depth-wise separable convolution with a dilated convolution. However, the simple c…
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
Many recent works on knowledge distillation have provided ways to transfer the knowledge of a trained network for improving the learning process of a new one, but finding a good te…
Context-aware Deep Feature Compression for High-speed Visual Tracking
Jongwon Choi, Hyung Jin Chang, Tobias Fischer +5
We propose a new context-aware correlation filter based tracking framework to achieve both high computational speed and state-of-the-art performance among real-time trackers. The m…