3 accepted papers
Brain-inspired spiking neural networks (SNNs) have the capability of energy-efficient processing of temporal information. However, leveraging the rich dynamic characteristics of SNNs and prior works in artificial neural networks (ANNs) to construct an effective object detection model for visual task…
Transformer-based methods have achieved remarkable performance in event-based object detection, owing to the global modeling ability. However, they neglect the influence of non-event and noisy regions and process them uniformly, leading to high computational overhead. To mitigate computation cost, s…
Recently, some methods estimate depth maps by fusing several adjacent single-view depth probabilities. They have achieved promising performance in multi-view inconsistent areas, such as texture-less surfaces, reflective surfaces, and moving objects. However, these methods involve two new problems: t