1 citations · 2 across the 9 of their papers we have counts for
12 papers
Rate-distortion optimization for full-reference image quality metrics via stochastic Hessian estimates
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
Block-based video codecs select coding parameters based on the input by optimizing a rate-distortion trade-off. The conventional distortion choice, the sum of squared errors (SSE),…
Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms
Samuel Fernández-Menduiña, Amir Ziashahabi, Eduardo Pavez +2
Long-context LLM decoding reads the key-value (KV) cache at every step. Loading it takes longer than computing attention over it, so throughput is bandwidth-bound. Hence, reducing…
FaSST: Fast Sparsifying Secondary Transform
Darukeesan Pakiyarajah, Samuel Fernández-Menduiña, Eduardo Pavez +2
Data-dependent secondary transforms, which aim to decorrelate coefficients of a separable primary transform, can improve residual coding efficiency; however, their deployment is of…
Rate-Distortion Optimization for Ensembles of Non-Reference Metrics
Xin Xiong, Samuel Fernández-Menduiña, Eduardo Pavez +3
Non-reference metrics (NRMs) can assess the visual quality of images and videos without a reference, making them well-suited for the evaluation of user-generated content. Nonethele…
L2G-Net: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
Despite their theoretical advantages, spectral methods based on the graph Fourier transform (GFT) are seldom used in graph neural networks (GNNs) due to the cost of computing the e…
Wrapper-Aware Rate-Distortion Optimization in Feature Coding for Machines
Samuel Fernández-Menduiña, Hyomin Choi, Fabien Racapé +2
Feature coding for machines (FCM) is a lossy compression paradigm for split-inference. The transmitter encodes the outputs of the first part of a neural network before sending them…
INT-DTT+: Low-Complexity Data-Dependent Transforms for Video Coding
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega +4
Discrete trigonometric transforms (DTTs), such as the DCT-2 and the DST-7, are widely used in video codecs for their balance between coding performance and computational efficiency…
Avoiding Quality Saturation in UGC Compression Using Denoised References
Xin Xiong, Samuel Fernández-Menduiña, Eduardo Pavez +3
Video-sharing platforms must re-encode large volumes of noisy user-generated content (UGC) to meet streaming demands. However, conventional codecs, which aim to minimize the mean s…
Rate-Distortion Optimization with Non-Reference Metrics for UGC Compression
Samuel Fernández-Menduiña, Xin Xiong, Eduardo Pavez +3
Service providers must encode a large volume of noisy videos to meet the demand for user-generated content (UGC) in online video-sharing platforms. However, low-quality UGC challen…
Image Coding for Machines via Feature-Preserving Rate-Distortion Optimization
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
Many images and videos are primarily processed by computer vision algorithms, involving only occasional human inspection. When this content requires compression before processing,…
Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
This paper develops fast graph Fourier transform (GFT) algorithms with O(n log n) runtime complexity for rank-one updates of the path graph. We first show that several commonly-use…
Image Coding via Perceptually Inspired Graph Learning
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
Most codec designs rely on the mean squared error (MSE) as a fidelity metric in rate-distortion optimization, which allows to choose the optimal parameters in the transform domain…