Journals starting with aici

AICity21 * *AI City Challenge
* 5th AI City Challenge, The
* All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
* Box-Level Tube Tracking and Refinement for Vehicles Anomaly Detection
* City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones
* Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
* Contrastive Learning for Natural Language-Based Vehicle Retrieval
* Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing
* DUN: Dual-path Temporal Matching Network for Natural Language-based Vehicle Retrieval
* Efficient Approach for Anomaly Detection in Traffic Videos, An
* Empirical Study of Vehicle Re-Identification on the AI City Challenge, An
* Fast Vehicle Turning-Movement Counting using Localization-based Tracking
* Keyword-based Vehicle Retrieval
* Multi-Camera Tracking By Candidate Intersection Ratio Tracklet Matching
* Multi-Camera Vehicle Tracking System based on City-Scale Vehicle Re-ID and Spatial-Temporal Information, A
* Multi-Camera Vehicle Tracking System Based on Spatial-Temporal Filtering
* Multi-Class Multi-Movement Vehicle Counting Based on CenterTrack
* Multi-Target Multi-Camera Vehicle Tracking for City-Scale Traffic Management
* Occlusion-aware Multi-target Multi-camera Tracking System, An
* Practices and A Strong Baseline for Traffic Anomaly Detection
* Progressive Data Mining and Adaptive Weighted Multi-Model Ensemble for Vehicle Re-Identification
* Real-time and Robust System for Counting Movement-Specific Vehicle at Crowded Intersections
* Region-and-Trajectory Movement Matching for Multiple Turn-counts at Road Intersection on Edge Device, A
* Robust and Online Vehicle Counting at Crowded Intersections
* Robust MTMC Tracking System for AI-City Challenge 2021, A
* Robust Vehicle Re-identification via Rigid Structure Prior
* SBNet: Segmentation-based Network for Natural Language-based Vehicle Search
* Strong Baseline for Vehicle Re-Identification, A
* TIED: A Cycle Consistent Encoder-Decoder Model for Text-to-Image Retrieval
* Tiny-PIRATE: A Tiny model with Parallelized Intelligence for Real-time Analysis as a Traffic countEr
* Towards Accurate Visual and Natural Language-Based Vehicle Retrieval Systems
* Tracklet-refined Multi-Camera Tracking based on Balanced Cross-Domain Re-Identification for Vehicles
* Traffic Video Event Retrieval via Text Query using Vehicle Appearance and Motion Attributes
* Vehicle Re-Identification based on Ensembling Deep Learning Features including a Synthetic Training Dataset, Orientation and Background Features, and Camera Verification.
* Vision-based System for Traffic Anomaly Detection using Deep Learning and Decision Trees, A
35 for AICity21

AICity22 * *AI City Challenge
* 6th AI City Challenge, The
* Box-Grained Reranking Matching for Multi-Camera Multi-Target Tracking
* City-Scale Multi-Camera Vehicle Tracking based on Space-Time-Appearance Features
* Coarse-to-Fine Boundary Localization method for Naturalistic Driving Action Recognition, A
* DeepACO: A Robust Deep Learning-based Automatic Checkout System
* Density-Guided Label Smoothing for Temporal Localization of Driving Actions
* Detecting Vehicles on the Edge: Knowledge Distillation to Improve Performance in Heterogeneous Road Traffic
* Effective Framework of Multi-Class Product Counting and Recognition for Automated Retail Checkout, An
* Effective Temporal Localization Method with Multi-View 3D Action Recognition for Untrimmed Naturalistic Driving Videos, An
* Federated Learning-based Driver Activity Recognition for Edge Devices
* Improving Multi-Target Multi-Camera Tracking by Track Refinement and Completion
* Key Point-Based Driver Activity Recognition
* Learning Generalized Feature for Temporal Action Detection: Application for Natural Driving Action Recognition Challenge
* Multi-Camera Multi-Vehicle Tracking with Domain Generalization and Contextual Constraints
* Multi-Camera Vehicle Tracking Based on Occlusion-aware and Inter-vehicle Information
* Multi-Camera Vehicle Tracking System for AI City Challenge 2022
* Multi-granularity Retrieval System for Natural Language-based Vehicle Retrieval, A
* MV-TAL: Mulit-view Temporal Action Localization in Naturalistic Driving
* Natural Language-Based Vehicle Retrieval with Explicit Cross-Modal Representation Learning
* OMG: Observe Multiple Granularities for Natural Language-Based Vehicle Retrieval
* PAND: Precise Action Recognition on Naturalistic Driving
* PersonGONE: Image Inpainting for Automated Checkout Solution
* Region-Based Deep Learning Approach to Automated Retail Checkout, A
* Robust Traffic-Aware City-Scale Multi-Camera Vehicle Tracking Of Vehicles, A
* Stargazer: A Transformer-based Driver Action Detection System for Intelligent Transportation
* Symmetric Network with Spatial Relationship Modeling for Natural Language-based Vehicle Retrieval
* Temporal Driver Action Localization using Action Classification Methods
* Text Query based Traffic Video Event Retrieval with Global-Local Fusion Embedding
* Tracked-Vehicle Retrieval by Natural Language Descriptions With Domain Adaptive Knowledge
* VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout
31 for AICity22

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