most citedState Space Model for New-Generation Network Alternative to Transformers: A Survey

19 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

MambaEVT: Event Stream based Visual Object Tracking using State Space Model

Xiao Wang, Chao wang, Shiao Wang +4

Event camera-based visual tracking has drawn more and more attention in recent years due to the unique imaging principle and advantages of low energy consumption, high dynamic rang…

cs.CV20242 cited

Event Stream based Human Action Recognition: A High-Definition Benchmark Dataset and Algorithms

Xiao Wang, Shiao Wang, Pengpeng Shao +3

Human Action Recognition (HAR) stands as a pivotal research domain in both computer vision and artificial intelligence, with RGB cameras dominating as the preferred tool for invest…

cs.CV2024

Mamba-FETrack: Frame-Event Tracking via State Space Model

Ju Huang, Shiao Wang, Shuai Wang +3

RGB-Event based tracking is an emerging research topic, focusing on how to effectively integrate heterogeneous multi-modal data (synchronized exposure video frames and asynchronous…

cs.LG202419 cited

State Space Model for New-Generation Network Alternative to Transformers: A Survey

Xiao Wang, Shiao Wang, Yuhe Ding +13

In the post-deep learning era, the Transformer architecture has demonstrated its powerful performance across pre-trained big models and various downstream tasks. However, the enorm…

cs.CV20231 cited

Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline

Xiao Wang, Shiao Wang, Chuanming Tang +4

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or direc…