… In Section IV, we describe our experimental setting and the benchmark datasets. Sections
V and VI summarize our experimental results, comparison, and discussions. The last section …

… We have also presented the state-of-the-art algorithms in a tabular form that give the best
performance on such datasets. In comparison with earlier surveys, our works give a better …

… To find out if an action recognition model is biased towards the non-action labels, we design
two evaluation protocols based on Kinetics-400 [7]: re-distributing the existing train-val split …

… The toolbox supports a wide variety of skeleton action recognition algorithms, … benchmarks
for skeleton-based action recognition. PYSKL has implemented six representative algorithms …

… We systematically benchmark state-of-the-art approaches on M2I dataset … algorithm [78]
can be used to solve (3). At last, K-nearest neighbor algorithm was applied for action recognition…

… will be analyzed and evaluated using five benchmark … HDG algorithm, and applied it in
cross-view action recognition … of-the-art algorithms for cross-view action recognition. Keywords: …

… of human action recognition. Since the first work reported in 2010 [8], many benchmark …
development and evaluation of new action recognition algorithms. However, available RGB-…

… Previous datasets used to benchmark pose estimation or action recognition algorithms are
… Despite all the modifications to the Dense Trajectories algorithm using low-to-mid ground …

… benchmark network for micro-action recognition, namely Micro-… Action Recognition Benchmarks
In this work, we evaluate nine existing algorithms specifically designed for generic action …

… To explore the effectiveness of the Mamba network in event-based human action recognition
tasks, in this work, we propose a novel action recognition framework based on a spatial-…