A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …

Human-centric visual tasks have attracted increasing research attention due to their
widespread applications. In this paper, we aim to learn a general human representation from …

Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

Abstract Multi-Target Multi-Camera tracking is a fundamental task for intelligent traffic
systems. The track 1 of AI City Challenge 2022 aims at the city-scale multi-camera vehicle …

Multi-target multi-camera tracking of persons in indoor scenarios such as retail stores or
warehouses enables efficient placement of products and improvement of working …

This paper presents a solution for Track 1 of the AI City Challenge 2023, which involves
Multi-Camera People Tracking in indoor scenarios. The proposed framework comprises four …

Multi-camera person tracking has gained significant attention in recent times, owing to its
widespread application in surveillance scenarios. However, this task is challenging due to …

Abstract Multi-Camera Multi-Target tracking (MCMT) is an essential task in intelligent
transportation systems. It is highly challenging due to several problems such as heavy …

Multi-camera tracking of vehicles on a city-wide level is a core component of modern traffic
monitoring systems. For this task, single-camera tracking failures are the most common …