16 citations · 45 across the 22 of their papers we have counts for
5 papers · 2 filters
On the Consistency of Video Large Language Models in Temporal Comprehension
Minjoon Jung, Junbin Xiao, Byoung-Tak Zhang +1
Video large language models (Video-LLMs) can temporally ground language queries and retrieve video moments. Yet, such temporal comprehension capabilities are neither well-studied n…
Scene-Text Grounding for Text-Based Video Question Answering
Sheng Zhou, Junbin Xiao, Xun Yang +5
Existing efforts in text-based video question answering (TextVideoQA) are criticized for their opaque decisionmaking and heavy reliance on scene-text recognition. In this paper, we…
Question-Answering Dense Video Events
Hangyu Qin, Junbin Xiao, Angela Yao
This paper presents question-answering on dense video events, a novel task that answers and grounds dense-event questions in long videos, thus challenging MLLMs to faithfully compr…
VideoQA in the Era of LLMs: An Empirical Study
Junbin Xiao, Nanxin Huang, Hangyu Qin +8
Video Large Language Models (Video-LLMs) are flourishing and has advanced many video-language tasks. As a golden testbed, Video Question Answering (VideoQA) plays pivotal role in V…
Abductive Ego-View Accident Video Understanding for Safe Driving Perception
Jianwu Fang, Lei-lei Li, Junfei Zhou +5
We present MM-AU, a novel dataset for Multi-Modal Accident video Understanding. MM-AU contains 11,727 in-the-wild ego-view accident videos, each with temporally aligned text descri…