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20202026
most citedTraining with Product Digital Twins for AutoRetail Checkout

1 citations · 2 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

The 10th AI City Challenge

Zheng Tang, Shuo Wang, David C. Anastasiu +34

The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical AI. Since its 2017 start with v…

cs.CV2026

From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning

Han Zhang, Yilin Zhao, Zaid Pervaiz Bhat +5

Detecting a traffic anomaly does not establish whether a video-language model can explain what happened, localize it in time, or identify its causes. We introduce TAR (Traffic Anom…

cs.CV2025

The 9th AI City Challenge

Zheng Tang, Shuo Wang, David C. Anastasiu +25

The ninth AI City Challenge continues to advance real-world applications of computer vision and AI in transportation, industrial automation, and public safety. The 2025 edition fea…

cs.CV2024

The 8th AI City Challenge

Shuo Wang, David C. Anastasiu, Zheng Tang +21

The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (I…

cs.CV2023★ 1 cited

Training with Product Digital Twins for AutoRetail Checkout

Yue Yao, Xinyu Tian, Zheng Tang +4

Automating the checkout process is important in smart retail, where users effortlessly pass products by hand through a camera, triggering automatic product detection, tracking, and…

cs.CV2023★ 1 cited

The Staged Knowledge Distillation in Video Classification: Harmonizing Student Progress by a Complementary Weakly Supervised Framework

Chao Wang, Zheng Tang

In the context of label-efficient learning on video data, the distillation method and the structural design of the teacher-student architecture have a significant impact on knowled…