Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial
neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal …

Temporal video grounding (TVG) is a critical task in video content understanding, requiring
precise alignment between video content and natural language instructions. Despite …

Event cameras exhibit remarkable attributes such as high dynamic range asynchronicity and
low latency making them highly suitable for vision tasks that involve high-speed motion in …

Eye tracking is crucial for human-computer interaction in different domains. Conventional
cameras encounter challenges such as power consumption and image quality during …

Event cameras, drawing inspiration from biological systems, efficiently detect changes in
ambient light with low latency and high dynamic range while consuming minimal power. The …

Spiking Neural Networks (SNNs), as the third generation of neural networks, have gained
prominence for their biological plausibility and computational efficiency, especially in …

Currently, neural-network processing in machine learning applications relies on layer
synchronization, whereby neurons in a layer aggregate incoming currents from all neurons …

Event-based motion field estimation is an important task. However, current optical flow
methods face challenges: learning-based approaches, often frame-based and relying on …

Skeleton-based multi-entity action recognition is a challenging task aiming to identify
interactive actions or group activities involving multiple diverse entities. Existing models for …

Event cameras are biologically inspired sensors that emit events asynchronously with
remarkable temporal resolution, garnering significant attention from both industry and …