3 papers
cs.CV2025
Vim-F: Visual State Space Model Benefiting from Learning in the Frequency Domain
Juntao Zhang, Shaogeng Liu, Jun Zhou +5
In recent years, State Space Models (SSMs) with efficient hardware-aware designs, known as the Mamba deep learning models, have made significant progress in modeling long sequences…
cs.CV2025
A Separable Self-attention Inspired by the State Space Model for Computer Vision
Juntao Zhang, Shaogeng Liu, Kun Bian +5
Mamba is an efficient State Space Model (SSM) with linear computational complexity. Although SSMs are not suitable for handling non-causal data, Vision Mamba (ViM) methods still de…
cs.CV2024
CoDeF: Content Deformation Fields for Temporally Consistent Video Processing
Hao Ouyang, Qiuyu Wang, Yuxi Xiao +6
We present the content deformation field CoDeF as a new type of video representation, which consists of a canonical content field aggregating the static contents in the entire vide…