311 citations · 332 across the 10 of their papers we have counts for
11 papers
InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Yixuan Zhu, Haolin Wang, Ao Li +6
Image enhancement finds wide-ranging applications in real-world scenarios due to complex environments and the inherent limitations of imaging devices. Recent diffusion-based method…
DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers
Minglei Shi, Ziyang Yuan, Haotian Yang +10
Diffusion models have demonstrated remarkable success in various image generation tasks, but their performance is often limited by the uniform processing of inputs across varying c…
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou +1
Diffusion probabilistic models (DPMs) have shown remarkable performance in visual synthesis but are computationally expensive due to the need for multiple evaluations during the sa…
FlowIE: Efficient Image Enhancement via Rectified Flow
Yixuan Zhu, Wenliang Zhao, Ao Li +3
Image enhancement holds extensive applications in real-world scenarios due to complex environments and limitations of imaging devices. Conventional methods are often constrained by…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…