1 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Latent-Shift: Gradient of Entropy Helps Neural Codecs
Muhammet Balcilar, Bharath Bhushan Damodaran, Karam Naser +2
End-to-end image/video codecs are getting competitive compared to traditional compression techniques that have been developed through decades of manual engineering efforts. These t…
Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression
Muhammet Balcilar, Bharath Damodaran, Pierre Hellier
End-to-end deep trainable models are about to exceed the performance of the traditional handcrafted compression techniques on videos and images. The core idea is to learn a non-lin…
Video Coding Using Learned Latent GAN Compression
Mustafa Shukor, Bharath Bhushan Damodaran, Xu Yao +1
We propose in this paper a new paradigm for facial video compression. We leverage the generative capacity of GANs such as StyleGAN to represent and compress a video, including intr…