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Found 7 papers, 3 papers with code
ALiSNet: Accurate and Lightweight Human Segmentation Network for Fashion E-Commerce
We obtain our final model, ALiSNet, with a size of 4MB and 97. 6$\pm$1. 0$\%$ mIoU, compared to Apple Person Segmentation, which has an accuracy of 94. 4$\pm$5. 7$\%$ mIoU on our dataset.
Neural Face Video Compression using Multiple Views
Recent advances in deep generative models led to the development of neural face video compression codecs that use an order of magnitude less bandwidth than engineered codecs.
Gradient flow encoding with distance optimization adaptive step size
In this work, we investigate a decoder-only method that uses gradient flow to encode data samples in the latent space.
Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE
We propose a method to model 3D MR brain volumes distribution by combining a 2D slice VAE with a Gaussian model that captures the relationships between slices.
Do Deep Neural Networks Suffer from Crowding?
Also, for all tested networks, when trained on targets in isolation, we find that recognition accuracy of the networks decreases the closer the flankers are to the target and the more flankers there are.
Query-adaptive Video Summarization via Quality-aware Relevance Estimation
Although the problem of automatic video summarization has recently received a lot of attention, the problem of creating a video summary that also highlights elements relevant to a search query has been less studied.
Predicting When Saliency Maps Are Accurate and Eye Fixations Consistent
Many computational models of visual attention use image features and machine learning techniques to predict eye fixation locations as saliency maps.
