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Found 5 papers, 1 papers with code
A Simple and Effective Point-based Network for Event Camera 6-DOFs Pose Relocalization
These cameras implicitly capture movement and depth information in events, making them appealing sensors for Camera Pose Relocalization (CPR) tasks.
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
We link the degraded accuracy to the vanishing of gradient on the temporal dimension through the analytical and experimental study of the training process of Leaky Integrate-and-Fire (LIF) Neuron-based SNNs.
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition
Moreover, it also achieves SOTA performance across all methods on three datasets, utilizing approximately 0. 3\% of the parameters and 0. 5\% of power consumption employed by artificial neural networks (ANNs).
TTPOINT: A Tensorized Point Cloud Network for Lightweight Action Recognition with Event Cameras
In the experiment, TTPOINT emerged as the SOTA method on three datasets while also attaining SOTA among point cloud methods on all five datasets.
Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation
To improve the accuracy of these models, some researchers have attempted to simulate human analogical reasoning to correct predictions for testing data by drawing analogies with the prediction errors of similar training data.
