2,685 research outputs found
Overview of intermittency analysis in heavy-ion collisions
In this paper, a search for power-law fluctuations with fractality and
intermittency analysis to explore the QCD phase diagram and the critical point
is summarized. Experimental data on self-similar correlations and fluctuations
with respect to the size of phase space volume in various high energy heavy-ion
collisions are presented, with special emphasis on background subtraction and
efficiency correction of the measurement. Phenomenological modelling and
theoretical work on the subject are discussed. Finally, we highlight possible
directions for future research.Comment: Invited brief review from MPLA, modified according to the journal
requirement and a few typos correcte
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
This paper considers the domain adaptive person re-identification (re-ID)
problem: learning a re-ID model from a labeled source domain and an unlabeled
target domain. Conventional methods are mainly to reduce feature distribution
gap between the source and target domains. However, these studies largely
neglect the intra-domain variations in the target domain, which contain
critical factors influencing the testing performance on the target domain. In
this work, we comprehensively investigate into the intra-domain variations of
the target domain and propose to generalize the re-ID model w.r.t three types
of the underlying invariance, i.e., exemplar-invariance, camera-invariance and
neighborhood-invariance. To achieve this goal, an exemplar memory is introduced
to store features of the target domain and accommodate the three invariance
properties. The memory allows us to enforce the invariance constraints over
global training batch without significantly increasing computation cost.
Experiment demonstrates that the three invariance properties and the proposed
memory are indispensable towards an effective domain adaptation system. Results
on three re-ID domains show that our domain adaptation accuracy outperforms the
state of the art by a large margin. Code is available at:
https://github.com/zhunzhong07/ECNComment: To appear in CVPR 201
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