83 citations · 108 across the 8 of their papers we have counts for
7 papers · 1 filter
Accelerating Diffusion Models with One-to-Many Knowledge Distillation
Linfeng Zhang, Kaisheng Ma
Significant advancements in image generation have been made with diffusion models. Nevertheless, when contrasted with previous generative models, diffusion models face substantial…
Revisiting Data Augmentation in Model Compression: An Empirical and Comprehensive Study
Muzhou Yu, Linfeng Zhang, Kaisheng Ma
The excellent performance of deep neural networks is usually accompanied by a large number of parameters and computations, which have limited their usage on the resource-limited ed…
CORSD: Class-Oriented Relational Self Distillation
Muzhou Yu, Sia Huat Tan, Kailu Wu +3
Knowledge distillation conducts an effective model compression method while holding some limitations:(1) the feature based distillation methods only focus on distilling the feature…
Structured Knowledge Distillation Towards Efficient and Compact Multi-View 3D Detection
Linfeng Zhang, Yukang Shi, Hung-Shuo Tai +4
Detecting 3D objects from multi-view images is a fundamental problem in 3D computer vision. Recently, significant breakthrough has been made in multi-view 3D detection tasks. Howev…
Region-aware Knowledge Distillation for Efficient Image-to-Image Translation
Linfeng Zhang, Xin Chen, Runpei Dong +1
Recent progress in image-to-image translation has witnessed the success of generative adversarial networks (GANs). However, GANs usually contain a huge number of parameters, which…
PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection
Linfeng Zhang, Runpei Dong, Hung-Shuo Tai +1
The remarkable breakthroughs in point cloud representation learning have boosted their usage in real-world applications such as self-driving cars and virtual reality. However, thes…