9 papers · 1 filter
DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation
Mingji Ge, Qirui Chen, Zeqian Li +1
Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora, like HowTo100M, offer rich…
EgoExo-Gen: Ego-centric Video Prediction by Watching Exo-centric Videos
Jilan Xu, Yifei Huang, Baoqi Pei +6
Generating videos in the first-person perspective has broad application prospects in the field of augmented reality and embodied intelligence. In this work, we explore the cross-vi…
Learning Streaming Video Representation via Multitask Training
Yibin Yan, Jilan Xu, Shangzhe Di +6
Understanding continuous video streams plays a fundamental role in real-time applications including embodied AI and autonomous driving. Unlike offline video understanding, streamin…
Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning
Baoqi Pei, Yifei Huang, Jilan Xu +8
In egocentric video understanding, the motion of hands and objects as well as their interactions play a significant role by nature. However, existing egocentric video representatio…
Enhancing Video-LLM Reasoning via Agent-of-Thoughts Distillation
Yudi Shi, Shangzhe Di, Qirui Chen +1
This paper tackles the problem of video question answering (VideoQA), a task that often requires multi-step reasoning and a profound understanding of spatial-temporal dynamics. Whi…
Grounded Multi-Hop VideoQA in Long-Form Egocentric Videos
Qirui Chen, Shangzhe Di, Weidi Xie
This paper considers the problem of Multi-Hop Video Question Answering (MH-VidQA) in long-form egocentric videos. This task not only requires to answer visual questions, but also t…