9,584 research outputs found
Discussion of "EQUI-energy sampler" by Kou, Zhou and Wong
Discussion of ``EQUI-energy sampler'' by Kou, Zhou and Wong [math.ST/0507080]Comment: Published at http://dx.doi.org/10.1214/009053606000000506 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
CERN: Confidence-Energy Recurrent Network for Group Activity Recognition
This work is about recognizing human activities occurring in videos at
distinct semantic levels, including individual actions, interactions, and group
activities. The recognition is realized using a two-level hierarchy of Long
Short-Term Memory (LSTM) networks, forming a feed-forward deep architecture,
which can be trained end-to-end. In comparison with existing architectures of
LSTMs, we make two key contributions giving the name to our approach as
Confidence-Energy Recurrent Network -- CERN. First, instead of using the common
softmax layer for prediction, we specify a novel energy layer (EL) for
estimating the energy of our predictions. Second, rather than finding the
common minimum-energy class assignment, which may be numerically unstable under
uncertainty, we specify that the EL additionally computes the p-values of the
solutions, and in this way estimates the most confident energy minimum. The
evaluation on the Collective Activity and Volleyball datasets demonstrates: (i)
advantages of our two contributions relative to the common softmax and
energy-minimization formulations and (ii) a superior performance relative to
the state-of-the-art approaches.Comment: Accepted to IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), 201
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