IEEE SPS SCV – Complexity-Aware Visual Signal Coding: Learning-Based Approaches for Energy Efficiency

Visual signal coding involves a great number of complex and computationally intensive decisions, especially in modern standards such as Versatile Video Coding (VVC), AOMedia Video 1 (AV1), and Video-based Point Cloud Compression (V-PCC). As multimedia applications increasingly target energy-constrained devices, reducing the computational and energy demands of coding systems becomes crucial. In this talk, we present how machine learning techniques can be applied to accelerate decision processes and significantly reduce complexity in these advanced coding standards. The talk will present examples in which trained models are implemented into both software codecs and hardware designs, and demonstrate how they can be combined with low-power techniques such as operand isolation, clock gating, and approximate computing. The presented approaches aim to enable efficient multimedia processing even under strict energy limitations.
Speaker(s): Guilherme Corrêa
Virtual: https://events.vtools.ieee.org/m/483053