6 accepted papers
Although multi-scale alignment has improved domain adaptive object detection by addressing data distribution differences and annotation challenges, little attention has been given to class distribution differences between domains. Additionally, the utilization of feature information across different…
In the rapidly evolving field of natural language processing, dialogue systems primarily employ a single-step dialogue paradigm. Although this paradigm is commonly adopted, it lacks the depth and fluidity of human interactions and does not appear natural. We introduce a novel **Step**-by-Step Dialog…
Video Anomaly Detection (VAD) is crucial for enhancing security and surveillance systems through automatic identification of irregular events, thereby enabling timely responses and augmenting overall situational awareness. Although existing methods have achieved decent detection performances on benc…
Modeling the interactions among agents based on their historical trajectories is key to precise multi-agent trajectory prediction. Hypergraph Convolutional Networks (HGCN) have become a proper choice for capturing high-order interactions among agents in this field. However, most existing works only…
Video Anomaly Detection (VAD) is a critical technology for intelligent surveillance systems and remains a challenging task in the signal processing community. An intuitive idea for VAD is to use a two-stream network to learn appearance and motion normality, respectively. However, existing approaches…
Violence detection is an essential and challenging problem in the computer vision community. Most existing works focus on single modal data analysis, which is not effective when multi-modality is available. Therefore, we propose a two-stage multi-modal information fusion method for violence detectio…