3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
Open-Vocabulary Spatio-Temporal Action Detection
Tao Wu, Shuqiu Ge, Jie Qin +2
Spatio-temporal action detection (STAD) is an important fine-grained video understanding task. Current methods require box and label supervision for all action classes in advance.…
STMixer: A One-Stage Sparse Action Detector
Tao Wu, Mengqi Cao, Ziteng Gao +2
Traditional video action detectors typically adopt the two-stage pipeline, where a person detector is first employed to generate actor boxes and then 3D RoIAlign is used to extract…
SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos
Tao Wu, Runyu He, Gangshan Wu +1
Video-based visual relation detection tasks, such as video scene graph generation, play important roles in fine-grained video understanding. However, current video visual relation…
Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation
Jiaming Zhang, Yutao Cui, Gangshan Wu +1
Current prevailing Video Object Segmentation methods follow the pipeline of extraction-then-matching, which first extracts features on current and reference frames independently, a…