Alpha-VL/ConvMAE
quality grade D, 43 out of 100ConvMAE: Masked Convolution Meets Masked Autoencoders
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Detection, segmentation, tracking, OCR models, 3D reconstruction and classical vision.
Signals: computer-vision, object-detection, image-segmentation, yolo, opencv, image-classification, pose-estimation, object-tracking
1,478 results
ConvMAE: Masked Convolution Meets Masked Autoencoders
This project is dedicated to the implementation and research of Kolmogorov-Arnold convolutional networks. The repository includes implementations of 1D, 2D, and 3D convolutions with different kernels, ResNet-like and DenseNet-like models, training code based on accelerate/PyTorch, as well as scripts for experiments with CIFAR-10 and Tiny ImageNet.
Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral
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