activity
20172025
most citedColor Learning for Image Compression

8 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2025

TreeNet: A Light Weight Model for Low Bitrate Image Compression

Mahadev Prasad Panda, Purnachandra Rao Makkena, Srivatsa Prativadibhayankaram +2

Reducing computational complexity remains a critical challenge for the widespread adoption of learning-based image compression techniques. In this work, we propose TreeNet, a novel…

eess.IV2024

A Study on the Effect of Color Spaces in Learned Image Compression

Srivatsa Prativadibhayankaram, Mahadev Prasad Panda, Jürgen Seiler +4

In this work, we present a comparison between color spaces namely YUV, LAB, RGB and their effect on learned image compression. For this we use the structure and color based learned…

eess.IV2024★ 4 cited

Efficient Learned Wavelet Image and Video Coding

Anna Meyer, Srivatsa Prativadibhayankaram, André Kaup

Learned wavelet image and video coding approaches provide an explainable framework with a latent space corresponding to a wavelet decomposition. The wavelet image coder iWave++ ach…

eess.IV2024

SLIC: A Learned Image Codec Using Structure and Color

Srivatsa Prativadibhayankaram, Mahadev Prasad Panda, Thomas Richter +3

We propose the structure and color based learned image codec (SLIC) in which the task of compression is split into that of luminance and chrominance. The deep learning model is bui…

eess.IV2023★ 8 cited

Color Learning for Image Compression

Srivatsa Prativadibhayankaram, Thomas Richter, Heiko Sparenberg +1

Deep learning based image compression has gained a lot of momentum in recent times. To enable a method that is suitable for image compression and subsequently extended to video com…

cs.CV2017

Compressive Online Robust Principal Component Analysis with Optical Flow for Video Foreground-Background Separation

Srivatsa Prativadibhayankaram, Huynh Van Luong, Thanh-Ha Le +1

In the context of online Robust Principle Component Analysis (RPCA) for the video foreground-background separation, we propose a compressive online RPCA with optical flow that sepa…