Meanwhile, inClust+ could integrate multimodal dataset to achieve multi-domain translation, as cross-modal autoencoder [21]. Input-mask and output-mask make inClust+ into multiple independent and related encoder-decoder combinations. Therefore, inClust+ can not only compress and reconstruct ...
pythonmachine-learningcomputer-visiondeep-learningautoencoderresnetunetconvolutional-neural-networkinpaintingface-masktensorflow2 UpdatedMay 15, 2021 Jupyter Notebook Face mask detection on Raspberry Pi 4 deep-learningubuntucppface-recognitionface-detectionaarch64armv8paddlepaddlessd-modelface-maskncnnraspberry-pi...
The technique of facial attribute manipulation has found increasing application, but it remains challenging to restrict editing of attributes so that a face's unique details are preserved. In this paper, we introduce our method, which we call a mask-adversarial autoencoder (M-AAE). It combines ...
4.1. Experimental Setup For each dataset, we only train a single autoencoder, de- coder, and codebook with 1024 tokens on cropped 256x256 images for all the experiments. The image is always com- pressed by a fixed factor of 16, i.e. from H ˆ W to a grid of tokens in the size...
After that, they proposed a model based on the MobileNetV2 [32] architecture, followed by autoencoders, which were used to transform the high-dimensional output feature vector into low dimensions. Finally, they performed ablation studies with their proposed model with VGG16, EfficientNet [56] ...
SimMIM [60] is a simple but effective end-to-end masked autoencoder, in which masked and unmasked patch tokens are both adopted as an encoder input. Considering that the current masked autoencoder methods are mainly based on a transformer, A22MIM [18] is compatible with both CNN and a ...
autoencoder.py change licenses paths Jun 16, 2023 download_assets.py add imagenet-512 training Mar 5, 2024 eval_latent.py add imagenet-512 training Mar 5, 2024 evaluator.py change licenses paths Jun 16, 2023 extract_latent.py add imagenet-512 training Mar 5, 2024 fid.py update detector...
Ranjan, A., Bolkart, T., Sanyal, S. & Black, M. J. Generating 3D faces using convolutional mesh autoencoders.Proc. European Conference on Computer Vision, 704–720 (ECCV, 2018). Liu, F., Zhu, R., Zeng, D., Zhao, Q. & Liu, X. Disentangling features in 3D face shapes for jo...
orientation of each bubble in a bubbly jet flow using an autoencoder and a CNN classifier. To understand the detailed interactions between each phase, however, it is important to know the exact shape (not just the bounding box or fitted ellipse) of the gas–liquid interface, which has not ...
We propose DAEMA (Denoising Autoencoder with Mask Attention), an algorithm based on a denoising autoencoder architecture with an attention mechanism. While most imputation algorithms use incomplete inputs as they would use complete data - up to basic preprocessing (e.g. mean imputation) - DAEMA...