most citedExtreme Video Compression with Pre-trained Diffusion Models

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Learning predictable and robust neural representations by straightening image sequences

Xueyan Niu, Cristina Savin, Eero P. Simoncelli

Prediction is a fundamental capability of all living organisms, and has been proposed as an objective for learning sensory representations. Recent work demonstrates that in primate…

q-bio.NC2024

Manifold Transform by Recurrent Cortical Circuit Enhances Robust Encoding of Familiar Stimuli

Weifan Wang, Xueyan Niu, Tai-Sing Lee

A ubiquitous phenomenon observed throughout the primate hierarchical visual system is the sparsification of the neural representation of visual stimuli as a result of familiarizati…

cs.CL20241 cited

Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding

Weizhi Fei, Xueyan Niu, Guoqing Xie +4

Current Large Language Models (LLMs) face inherent limitations due to their pre-defined context lengths, which impede their capacity for multi-hop reasoning within extensive textua…

eess.IV20241 cited

Extreme Video Compression with Pre-trained Diffusion Models

Bohan Li, Yiming Liu, Xueyan Niu +3

Diffusion models have achieved remarkable success in generating high quality image and video data. More recently, they have also been used for image compression with high perceptua…

cs.IT2023

A Hybrid Wireless Image Transmission Scheme with Diffusion

Xueyan Niu, Xu Wang, Deniz Gündüz +3

We propose a hybrid joint source-channel coding (JSCC) scheme, in which the conventional digital communication scheme is complemented with a generative refinement component to impr…

cs.IT2023

Conditional Rate-Distortion-Perception Trade-Off

Xueyan Niu, Deniz Gündüz, Bo Bai +1

Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perce…