3 papers
cs.CV2026
SpikeTAD: Spiking Neural Networks for End-to-End Temporal Action Detection
Min Yang, Mi Zhou, Limin Wang
Video understanding is a crucial part of computer vision, with numerous application scenarios. With the increasing popularity of mobile devices, an increasing number of efforts are…
cs.CV2026
Temporal2Seq: A Unified Framework for Temporal Video Understanding Tasks
Min Yang, Zichen Zhang, Qian Dang +1
With the development of video understanding, there is a proliferation of tasks for clip-level temporal video analysis, including temporal action detection (TAD), temporal action se…
cs.CV2025
MobileViCLIP: An Efficient Video-Text Model for Mobile Devices
Min Yang, Zihan Jia, Zhilin Dai +2
Efficient lightweight neural networks are with increasing attention due to their faster reasoning speed and easier deployment on mobile devices. However, existing video pre-trained…