# The 7th AI City Challenge

arXiv: https://arxiv.org/abs/2304.07500 · HTML: https://mlsanity.com/paper/2304.07500/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 71 references that are in the map.
- First posted on arXiv 15 Apr 2023.

## Builds on (most cited first, 29 of 29)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Deep High-Resolution Representation Learning for Human Pose Estimation](https://mlsanity.com/paper/1902.09212/) (2019)
- [VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training](https://mlsanity.com/paper/2203.12602/) (2022)
- [Simple Online and Realtime Tracking with a Deep Association Metric](https://mlsanity.com/paper/1703.07402/) (2017)
- [Simple Online and Realtime Tracking](https://mlsanity.com/paper/1602.00763/) (2016)
- [Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking](https://mlsanity.com/paper/1609.01775/) (2016)
- [MViTv2: Improved Multiscale Vision Transformers for Classification and Detection](https://mlsanity.com/paper/2112.01526/) (2021)
- [BMN: Boundary-Matching Network for Temporal Action Proposal Generation](https://mlsanity.com/paper/1907.09702/) (2019)
- [BoT-SORT: Robust Associations Multi-Pedestrian Tracking](https://mlsanity.com/paper/2206.14651/) (2022)
- [ActionFormer: Localizing Moments of Actions with Transformers](https://mlsanity.com/paper/2202.07925/) (2022)
- [Omni-Scale Feature Learning for Person Re-Identification](https://mlsanity.com/paper/1905.00953/) (2019)
- [StrongSORT: Make DeepSORT Great Again](https://mlsanity.com/paper/2202.13514/) (2022)
- [CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification](https://mlsanity.com/paper/1903.09254/) (2019)
- [Unsupervised Pre-training for Person Re-identification](https://mlsanity.com/paper/2012.03753/) (2020)
- [Revisiting Anchor Mechanisms for Temporal Action Localization](https://mlsanity.com/paper/2008.09837/) (2020)
- [Self-Supervised Pre-Training for Transformer-Based Person Re-Identification](https://mlsanity.com/paper/2111.12084/) (2021)
- [NMS Strikes Back](https://mlsanity.com/paper/2212.06137/) (2022)
- [The 5th AI City Challenge](https://mlsanity.com/paper/2104.12233/) (2021)
- [CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions](https://mlsanity.com/paper/2101.04741/) (2021)
- [The 6th AI City Challenge](https://mlsanity.com/paper/2204.10380/) (2022)
- [Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition](https://mlsanity.com/paper/2304.07421/) (2023)
- [The 4th AI City Challenge](https://mlsanity.com/paper/2004.14619/) (2020)
- [Synthetic Distracted Driving (SynDD2) dataset for analyzing distracted behaviors and various gaze zones of a driver](https://mlsanity.com/paper/2204.08096/) (2022)
- [Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8](https://mlsanity.com/paper/2304.08256/) (2023)
- [Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond](https://mlsanity.com/paper/2202.14034/) (2022)
- [Recent Advancements in Deep Learning Applications and Methods for Autonomous Navigation: A Comprehensive Review](https://mlsanity.com/paper/2302.11089/) (2023)
- [DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving Videos](https://mlsanity.com/paper/2304.08261/) (2023)

## Built on by (most cited first, 20 of 20)

- [Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges](https://mlsanity.com/paper/2308.10407/) (2023)
- [The 8th AI City Challenge](https://mlsanity.com/paper/2404.09432/) (2024)
- [Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic Scenes](https://mlsanity.com/paper/2311.17948/) (2023)
- [Enhancing Multi-Camera People Tracking with Anchor-Guided Clustering and Spatio-Temporal Consistency ID Re-Assignment](https://mlsanity.com/paper/2304.09471/) (2023)
- [MCTR: Multi Camera Tracking Transformer](https://mlsanity.com/paper/2408.13243/) (2024)
- [The 10th AI City Challenge](https://mlsanity.com/paper/2608.17044/) (2026)
- [M2DAR: Multi-View Multi-Scale Driver Action Recognition with Vision Transformer](https://mlsanity.com/paper/2305.08877/) (2023)
- [TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios](https://mlsanity.com/paper/2311.18839/) (2023)
- [Evaluating Vision-Language Models for Zero-Shot Detection, Classification, and Association of Motorcycles, Passengers, and Helmets](https://mlsanity.com/paper/2408.02244/) (2024)
- [Driver Activity Classification Using Generalizable Representations from Vision-Language Models](https://mlsanity.com/paper/2404.14906/) (2024)
- [ATARS: An Aerial Traffic Atomic Activity Recognition and Temporal Segmentation Dataset](https://mlsanity.com/paper/2503.18553/) (2025)
- [VQPy: An Object-Oriented Approach to Modern Video Analytics](https://mlsanity.com/paper/2311.01623/) (2023)
- [VegaEdge: Edge AI Confluence Anomaly Detection for Real-Time Highway IoT-Applications](https://mlsanity.com/paper/2311.07880/) (2023)
- [Transformer-based Fusion of 2D-pose and Spatio-temporal Embeddings for Distracted Driver Action Recognition](https://mlsanity.com/paper/2403.06577/) (2024)
- [YOWO: You Only Walk Once to Jointly Map An Indoor Scene and Register Ceiling-mounted Cameras](https://mlsanity.com/paper/2511.16521/) (2025)
- [Co-Learning: Towards Semi-Supervised Object Detection with Road-side Cameras](https://mlsanity.com/paper/2411.19143/) (2024)
- [VisionGuard: Synergistic Framework for Helmet Violation Detection](https://mlsanity.com/paper/2506.21005/) (2025)
- [Fully Distributed Multi-View 3D Tracking in Real-Time](https://mlsanity.com/paper/2606.13127/) (2026)
- [Geometry Beats Estimated Depth: RGB-Only Multi-Camera 3D Tracking under Sim2Real](https://mlsanity.com/paper/2608.07579/) (2026)
- [Action-Slot: Structured Action-Centric Representation Learning for Multi-Agent Atomic Activity Understanding](https://mlsanity.com/paper/2609.24127/) (2026)

## Abstract (arXiv)

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 (ITS) - that have considerable untapped potential. The 2023 challenge had five tracks, which drew a record-breaking number of participation requests from 508 teams across 46 countries. Track 1 was a brand new track that focused on multi-target multi-camera (MTMC) people tracking, where teams trained and evaluated using both real and highly realistic synthetic data. Track 2 centered around natural-language-based vehicle track retrieval. Track 3 required teams to classify driver actions in naturalistic driving analysis. Track 4 aimed to develop an automated checkout system for retail stores using a single view camera. Track 5, another new addition, tasked teams with detecting violations of the helmet rule for motorcyclists. Two leader boards were released for submissions based on different methods: a public leader board for the contest where external private data wasn't allowed and a general leader board for all results submitted. The participating teams' top performances established strong baselines and even outperformed the state-of-the-art in the proposed challenge tracks.