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

19 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Event Stream-based Sign Language Translation: A High-Definition Benchmark Dataset and A Novel Baseline

Shiao Wang, Xiao Wang, Duoqing Yang +5

Sign Language Translation (SLT) is a core task in the field of AI-assisted disability. Traditional SLT methods are typically based on visible light videos, which are easily affecte…

eess.IV2024

Pre-training on High Definition X-ray Images: An Experimental Study

Xiao Wang, Yuehang Li, Wentao Wu +5

Existing X-ray based pre-trained vision models are usually conducted on a relatively small-scale dataset (less than 500k samples) with limited resolution (e.g., 224 224).…

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.CV2023

Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

Xiao Wang, Yao Rong, Shiao Wang +5

Pattern recognition based on RGB-Event data is a newly arising research topic and previous works usually learn their features using CNN or Transformer. As we know, CNN captures the…

cs.CV2023

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition

Xiao Wang, Yao Rong, Zongzhen Wu +4

Event camera-based pattern recognition is a newly arising research topic in recent years. Current researchers usually transform the event streams into images, graphs, or voxels, an…