4 citations · 7 across the 4 of their papers we have counts for
4 papers
Disentangled Action Recognition with Knowledge Bases
Zhekun Luo, Shalini Ghosh, Devin Guillory +3
Action in video usually involves the interaction of human with objects. Action labels are typically composed of various combinations of verbs and nouns, but we may not have trainin…
Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Variational autoencoder (VAE) estimates the posterior parameters (mean and variance) of latent variables corresponding to each input data. While it is used for many tasks, the tran…
Variable Rate Image Compression Method with Dead-zone Quantizer
Jing Zhou, Akira Nakagawa, Keizo Kato +3
Deep learning based image compression methods have achieved superior performance compared with transform based conventional codec. With end-to-end Rate-Distortion Optimization (RDO…
Rate-Distortion Optimization Guided Autoencoder for Isometric Embedding in Euclidean Latent Space
Keizo Kato, Jing Zhou, Tomotake Sasaki +1
To analyze high-dimensional and complex data in the real world, deep generative models, such as variational autoencoder (VAE) embed data in a low-dimensional space (latent space) a…