3 papers
cs.CV2026
SGTA: Scene-Graph Based Multi-Modal Traffic Agent for Video Understanding
Xingcheng Zhou, Mingyu Liu, Walter Zimmer +2
We present Scene-Graph Based Multi-Modal Traffic Agent (SGTA), a modular framework for traffic video understanding that combines structured scene graphs with multi-modal reasoning.…
cs.CV2025
TUMTraffic-VideoQA: A Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes
Xingcheng Zhou, Konstantinos Larintzakis, Hao Guo +7
We present TUMTraffic-VideoQA, a novel dataset and benchmark designed for spatio-temporal video understanding in complex roadside traffic scenarios. The dataset comprises 1,000 vid…
eess.IV2024
PointCompress3D: A Point Cloud Compression Framework for Roadside LiDARs in Intelligent Transportation Systems
Walter Zimmer, Ramandika Pranamulia, Xingcheng Zhou +2
In the context of Intelligent Transportation Systems (ITS), efficient data compression is crucial for managing large-scale point cloud data acquired by roadside LiDAR sensors. The…