K
Kaiming He
Researcher at Facebook
Publications - 140
Citations - 440003
Kaiming He is an academic researcher from Facebook. The author has contributed to research in topics: Object detection & Image segmentation. The author has an hindex of 89, co-authored 135 publications receiving 272091 citations. Previous affiliations of Kaiming He include The Chinese University of Hong Kong & Microsoft.
Papers
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Non-local Neural Networks
TL;DR: In this article, a non-local operation computes the response at a position as a weighted sum of the features at all positions, which can be used to capture long-range dependencies.
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Exploring Randomly Wired Neural Networks for Image Recognition
TL;DR: In this article, the authors explore a more diverse set of connectivity patterns through the lens of randomly wired neural networks and define the concept of a stochastic network generator that encapsulates the entire network generation process.
Proceedings ArticleDOI
A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
TL;DR: SlowFast as mentioned in this paper proposes a simple objective to encourage temporally-persistent features in the same video, and in spite of its simplicity, it works surprisingly well across: (i) different unsupervised frameworks, (ii) pre-training datasets, (iii) downstream datasets, and (iv) backbone architectures.
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Efficient and Accurate Approximations of Nonlinear Convolutional Networks
TL;DR: In this article, the reconstruction error of the nonlinear responses is minimized subject to a low-rank constraint, which helps to reduce the complexity of filters and reduces the accumulated error when multiple layers are approximated.
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Fast Guided Filter.
Kaiming He,Jian Sun +1 more
TL;DR: The guided filter can be simply sped up from O(N) time to O( N/s^2) time for a subsampling ratio s, leading to a speedup of >10x with almost no visible degradation.