Automatic Incident Detection Challenge 2026 (AID2026) aims to advance the state of the art in real-time accident and anomaly recognition in road-traffic video. Despite significant progress in video understanding, the reliable detection of road incidents remains an open challenge, largely due to the scarcity of datasets collected from fixed surveillance cameras. To address this gap, AID2026 provides the research community with dataset of 2,556 real-world traffic videos containing annotated incidents captured in real environments, along with a standardized evaluation protocol.
Crime Detection Challenge (CDC26) is an international competition organized to encourage participants to develop advanced methods for detecting crime events in real-world video. The challenge considers a wide range of situations found in surveillance applications, ranging from public spaces to semi-private environments such as retail stores, care facilities, and correctional institutions, where scene variability, occlusions, viewpoint changes, and heterogeneous video quality make reliable detection difficult.
The MicrosoftCMTservice was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.