Shot Event Detection

Shot event detection focuses on identifying specific events within data (text, audio, or images) using limited labeled examples, addressing the challenge of data scarcity in many real-world applications. Current research emphasizes methods like prototype-based and prompt-based learning, often incorporating contrastive learning and techniques to mitigate biases inherent in training data, with a strong focus on improving performance in few-shot and even zero-shot scenarios. These advancements are significant for various fields, enabling more efficient and robust event detection in applications ranging from bioacoustic monitoring to online news analysis and beyond.