try to implement the CVPR 2019 paper "Selective Kernel Networks" by PyTorch

Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (CVPR 2022)

[ICLR 2023] "More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity"; [ICML 2023] "Are Large Kernels Better Teachers than Transformers for ConvNets?"

[CVPR 2023] Code for PConv and FasterNet

[CVPR 2023 (Highlight)] Offical implementation of the paper "RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction".

This is an official pytorch implementation of Fast Fourier Convolution.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results