3 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts
Nuoyan Zhou, Zhijun Tu, Lei Yu +4
Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities in image generation. However,…
Mixture of Ranks with Degradation-Aware Routing for One-Step Real-World Image Super-Resolution
Xiao He, Zhijun Tu, Kun Cheng +4
The demonstrated success of sparsely-gated Mixture-of-Experts (MoE) architectures, exemplified by models such as DeepSeek and Grok, has motivated researchers to investigate their a…
One-Step Diffusion-based Real-World Image Super-Resolution with Visual Perception Distillation
Xue Wu, Jingwei Xin, Zhijun Tu +4
Diffusion-based models have been widely used in various visual generation tasks, showing promising results in image super-resolution (SR), while typically being limited by dozens o…
Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution
Junbo Qiao, Jincheng Liao, Wei Li +7
State Space Models (SSM), such as Mamba, have shown strong representation ability in modeling long-range dependency with linear complexity, achieving successful applications from h…
Effective Diffusion Transformer Architecture for Image Super-Resolution
Kun Cheng, Lei Yu, Zhijun Tu +7
Recent advances indicate that diffusion models hold great promise in image super-resolution. While the latest methods are primarily based on latent diffusion models with convolutio…