11 citations · 12 across the 7 of their papers we have counts for
7 papers
Constructive Approaches to Perception-Aware Lossy Source Coding: Information-Theoretic Guidelines
Ali Hussein, Jun Chen, Chao Tian +1
Perception-aware lossy source coding has attracted significant recent interest. It augments the classical distortion criterion with an explicit perception constraint, thereby enabl…
On Self-Adaptive Perception Loss Function for Sequential Lossy Compression
Sadaf Salehkalaibar, Buu Phan, Likun Cai +4
We consider causal, low-latency, sequential lossy compression, with mean squared-error (MSE) as the distortion loss, and a perception loss function (PLF) to enhance the realism of…
Source-Channel Separation Theorems for Distortion Perception Coding
Chao Tian, Jun Chen, Krishna Narayanan
It is well known that separation between lossy source coding and channel coding is asymptotically optimal under classical additive distortion measures. Recently, coding under a new…
Minimum Entropy Coupling with Bottleneck
M. Reza Ebrahimi, Jun Chen, Ashish Khisti
This paper investigates a novel lossy compression framework operating under logarithmic loss, designed to handle situations where the reconstruction distribution diverges from the…
Information Compression in the AI Era: Recent Advances and Future Challenges
Jun Chen, Yong Fang, Ashish Khisti +3
This survey articles focuses on emerging connections between the fields of machine learning and data compression. While fundamental limits of classical (lossy) data compression are…
Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources
Jingjing Qian, Sadaf Salehkalaibar, Jun Chen +5
This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source coding problem where the goal is to compress the multi-component source subject to dis…
Rate-Distortion-Perception Tradeoff Based on the Conditional-Distribution Perception Measure
Sadaf Salehkalaibar, Jun Chen, Ashish Khisti +1
This paper studies the rate-distortion-perception (RDP) tradeoff for a memoryless source model in the asymptotic limit of large block-lengths. The perception measure is based on a…