  A number of detections have been made in the past few years of gravitational
waves from compact binary coalescences. While there exist well-understood
waveform models for signals from compact binary coalescences, many sources of
gravitational waves are not well modeled, including potential long-transient
signals from a binary neutron star post-merger remnant. Searching for these
sources requires robust detection algorithms that make minimal assumptions
about any potential signals. In this paper, we compare two unmodeled search
schemes for long-transient gravitational waves, operating on cross-power
spectrograms. One is an efficient algorithm first implemented for continuous
wave searches, based on a hidden Markov model. The other is a seedless
clustering method, which has been used in transient gravitational wave analysis
in the past. We quantify the performance of both algorithms, including
sensitivity and computational cost, by simulating synthetic signals with a
special focus on sources like binary neutron star post-merger remnants. We
demonstrate that the hidden Markov model tracking is a good option in
model-agnostic searches for low signal-to-noise ratio signals. We also show
that it can outperform the seedless method for certain categories of signals
while also being computationally more efficient.
