2 papers
cs.CV2025
MixANT: Observation-dependent Memory Propagation for Stochastic Dense Action Anticipation
Syed Talal Wasim, Hamid Suleman, Olga Zatsarynna +2
We present MixANT, a novel architecture for stochastic long-term dense anticipation of human activities. While recent State Space Models (SSMs) like Mamba have shown promise throug…
cs.CV2025
StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos
Hamid Suleman, Syed Talal Wasim, Muzammal Naseer +1
State-space models (SSMs), exemplified by S4, have introduced a novel context modeling method by integrating state-space techniques into deep learning. However, they struggle with…