12 citations · 12 across the 3 of their papers we have counts for
4 papers
MUSE: Feature Self-Distillation with Mutual Information and Self-Information
Yu Gong, Ye Yu, Gaurav Mittal +2
We present a novel information-theoretic approach to introduce dependency among features of a deep convolutional neural network (CNN). The core idea of our proposed method, called…
Unsupervised Few-Shot Action Recognition via Action-Appearance Aligned Meta-Adaptation
Jay Patravali, Gaurav Mittal, Ye Yu +2
We present MetaUVFS as the first Unsupervised Meta-learning algorithm for Video Few-Shot action recognition. MetaUVFS leverages over 550K unlabeled videos to train a two-stream 2D…
Revisiting Dynamic Convolution via Matrix Decomposition
Yunsheng Li, Yinpeng Chen, Xiyang Dai +7
Recent research in dynamic convolution shows substantial performance boost for efficient CNNs, due to the adaptive aggregation of K static convolution kernels. It has two limitatio…
Stronger NAS with Weaker Predictors
Junru Wu, Xiyang Dai, Dongdong Chen +7
Neural Architecture Search (NAS) often trains and evaluates a large number of architectures. Recent predictor-based NAS approaches attempt to alleviate such heavy computation costs…