mingsun-tse / caffe_increg

[IJCNN'19, IEEE JSTSP'19] Caffe code for our paper "Structured Pruning for Efficient ConvNets via Incremental Regularization"; [BMVC'18] "Structured Probabilistic Pruning for Convolutional Neural Network Acceleration"

Hi there 👋

I am a Ph.D. candidate at SMILE Lab of Northeastern University (Boston, USA). Before that, I spent seven wonderful years at Zhejiang Univeristy (Hangzhou, China) to get my B.E. and M.S. degrees.

I am interested in a variety of topics in computer vision and machine learning. My research works orbit efficient deep learning (a.k.a. model compression), spanning from the most common image classifcation task (GReg, Awesome-PaI, TPP) to neural style transfer (Collaborative-Distillation), single image super-resolution (ASSL, SRP), and 3D novel view synthesis (R2L, MobileR2L).

I do my best towards easily reproducible research.

🔥 NEWS: [NeurIPS'23] We are excited to present SnapFusion, a super-efficient mobile diffusion model that can do text-to-image generation in less than 2s🚀 on mobile devices! [Arxiv] [Webpage]
🔥 NEWS: [CVPR'23] Check out our new blazing fast🚀 neural rendering model on mobile devices: MobileR2L (the lightweight version of R2L), can render 1008x756 images at 56fps on iPhone13 [Arxiv] [Code]
🔥 NEWS: [ICLR'23] Check out the very first trainability-preserving filter pruning method: TPP [Arxiv] [Code]
🔥 NEWS: Check out our preprint work that deciphers the so confusing benchmark situation in neural network (filter) pruning: [Arxiv] [Code]
✨ NEWS: Check out our investigation of what makes a "good" data augmentation in knowledge distillation, in NeurIPS 2022: [Webpage] [Code]
✨ NEWS: Check out our Efficient NeRF project via distillation, in ECCV 2022: [R2L]

caffe_increg's Issues

pruning

Hi ，I have some questions for your paper，then Why retraining the model after pruning? In this way, the parameters will reappear after pruning.Is it possible to accelerate?
I'm looking forward to your reply，thanks

The caffe file make runtest error