4 papers
Exploring Diffusion with Test-Time Training on Efficient Image Restoration
Rongchang Lu, Tianduo Luo, Yunzhi Jiang +4
Image restoration faces challenges including ineffective feature fusion, computational bottlenecks and inefficient diffusion processes. To address these, we propose DiffRWKVIR, a n…
Exploring Linear Attention Alternative for Single Image Super-Resolution
Rongchang Lu, Changyu Li, Donghang Li +3
Deep learning-based single-image super-resolution (SISR) technology focuses on enhancing low-resolution (LR) images into high-resolution (HR) ones. Although significant progress ha…
RWKV-X: A Linear Complexity Hybrid Language Model
Haowen Hou, Zhiyi Huang, Kaifeng Tan +2
In this paper, we introduce RWKV-X, a novel hybrid architecture that combines the efficiency of RWKV for short-range modeling with a sparse attention mechanism designed to capture…
Delta-WKV: A Novel Meta-in-Context Learner for MRI Super-Resolution
Rongchang Lu, Bingcheng Liao, Haowen Hou +2
Magnetic Resonance Imaging (MRI) Super-Resolution (SR) addresses the challenges such as long scan times and expensive equipment by enhancing image resolution from low-quality input…