In this paper, we explore a novel model reusing task tailored for graph
...
State-of-the-art parametric and non-parametric style transfer approaches...
In this paper, we study a novel meta aggregation scheme towards binarizi...
Multi-person pose estimation and tracking serve as crucial steps for vid...
We propose a dense indirect visual odometry method taking as input exter...
Graph convolutional networks (GCN) have recently demonstrated their pote...
Catastrophic forgetting refers to the tendency that a neural network
"fo...
Prior gradient-based attribution-map methods rely on handcrafted propaga...
Graphs have been widely adopted to denote structural connections between...
Existing knowledge distillation methods focus on convolutional neural
ne...
Existing knowledge distillation methods focus on convolutional neural
ne...
Semi-supervised wrapper methods are concerned with building effective
su...
This paper proposes a universal method, Boost Picking, to train supervis...