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Found 3 papers, 3 papers with code
Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layer
Building upon this, we have modified the batch normalization (BN) and ReLU layer preceding the fully connected layer, diminishing their impact on the output feature distributions and thereby widening the distribution gap between ID and OOD data features.
GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set
In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
In this paper we present a novel perspective, where a gait is regarded as a set consisting of independent frames.
Ranked #2 on
Multiview Gait Recognition
on OU-MVLP
