We tackle the problem of semantic boundary prediction, which aims to identify
pixels that belong to object(class) boundaries. We notice that relevant
datasets consist of a significant level of label noise, reflecting the fact
This dataset challenges the time series community with the task of
satellite-based vegetation identification on large scale real-world dataset of
satellite data acquired during one entire year. It consists of time series data
with associated crop...
We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE)
models for large scale image generation. To this end, we scale and enhance the
autoregressive priors used in VQ-VAE to generate synthetic samples of much
higher coherence and...