2 citations · 3 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
CaST-Bench: Benchmarking Causal Chain-Grounded Spatio-Temporal Reasoning for Video Question Answering
Mingfang Zhang, Jingjing Pan, Ashutosh Kumar +7
Cause-and-effect reasoning in video is a significant challenge for Vision-Language Models (VLMs), as it requires going beyond surface-level perception to a deeper understanding of…
InstAP: Instance-Aware Vision-Language Pre-Train for Spatial-Temporal Understanding
Ashutosh Kumar, Rajat Saini, Jingjing Pan +5
Current vision-language pre-training (VLP) paradigms excel at global scene understanding but struggle with instance-level reasoning due to global-only supervision. We introduce Ins…
WTS: A Pedestrian-Centric Traffic Video Dataset for Fine-grained Spatial-Temporal Understanding
Quan Kong, Yuki Kawana, Rajat Saini +8
In this paper, we address the challenge of fine-grained video event understanding in traffic scenarios, vital for autonomous driving and safety. Traditional datasets focus on drive…