4 accepted papers
Diffusion models have demonstrated outstanding performance in industrial anomaly detection. However, their iterative denoising nature results in slow inference speed, limiting their practicality for real-time industrial deployment. To address this challenge, we propose OmiAD, a one-step masked diffu…
Video highlight detection is important for video understanding, as it localizes the attractive regions in the video automatically. Because the fully-supervised video highlight is expensive for its frame-level annotation, we present a novel network for weakly-supervised video highlight detection base…
Boundary localization is a challenging problem in Temporal Action Detection (TAD), in which there are two main issues. First, the submergence of movement feature, i.e. the movement information in a snippet is covered by the scene information. Second, the scale of action, that is, the proportion of a…
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and…