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Found 3 papers, 2 papers with code
PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution
Due to these issues, current CNNs compromise to scale up to 51x51 in the form of stripe convolution (i. e., 51x5 + 5x51) and start to saturate as the kernel size continues growing.
Re-parameterizing Your Optimizers rather than Architectures
For the extreme simplicity of model structure, we focus on a VGG-style plain model and showcase that such a simple model trained with a RepOptimizer, which is referred to as RepOpt-VGG, performs on par with or better than the recent well-designed models.
RepMLPNet: Hierarchical Vision MLP with Re-parameterized Locality
Our results reveal that 1) Locality Injection is a general methodology for MLP models; 2) RepMLPNet has favorable accuracy-efficiency trade-off compared to the other MLPs; 3) RepMLPNet is the first MLP that seamlessly transfer to Cityscapes semantic segmentation.
Ranked #58 on
Semantic Segmentation
on Cityscapes val
