325 citations · 1k across the 29 of their papers we have counts for
29 papers
Transformer-based Image Compression
Ming Lu, Peiyao Guo, Huiqing Shi +2
A Transformer-based Image Compression (TIC) approach is developed which reuses the canonical variational autoencoder (VAE) architecture with paired main and hyper encoder-decoders.…
Which One is Better: Assessing Objective Metrics for Point Cloud Compression
Yipeng Liu, Qi Yang, Yiling Xu +1
Point cloud compression (PCC) has made remarkable achievement in recent years. In the mean time, point cloud quality assessment (PCQA) also realize gratifying development. Some rec…
End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation
Haojie Liu, Ming Lu, Zhiqi Chen +3
Recent years have witnessed rapid advances in learnt video coding. Most algorithms have solely relied on the vector-based motion representation and resampling (e.g., optical flow b…
ANT: Learning Accurate Network Throughput for Better Adaptive Video Streaming
Jiaoyang Yin, Yiling Xu, Hao Chen +3
Adaptive Bit Rate (ABR) decision plays a crucial role for ensuring satisfactory Quality of Experience (QoE) in video streaming applications, in which past network statistics are ma…
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
Ren Yang, Radu Timofte, Jing Liu +69
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Di…
Advances In Video Compression System Using Deep Neural Network: A Review And Case Studies
Dandan Ding, Zhan Ma, Di Chen +3
Significant advances in video compression system have been made in the past several decades to satisfy the nearly exponential growth of Internet-scale video traffic. From the appli…
Decomposition, Compression, and Synthesis (DCS)-based Video Coding: A Neural Exploration via Resolution-Adaptive Learning
Ming Lu, Tong Chen, Dandan Ding +2
Inspired by the facts that retinal cells actually segregate the visual scene into different attributes (e.g., spatial details, temporal motion) for respective neuronal processing,…
Multiscale Point Cloud Geometry Compression
Jianqiang Wang, Dandan Ding, Zhu Li +1
Recent years have witnessed the growth of point cloud based applications because of its realistic and fine-grained representation of 3D objects and scenes. However, it is a challen…
Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model
Haojie Liu, Ming Lu, Zhan Ma +4
Over the past two decades, traditional block-based video coding has made remarkable progress and spawned a series of well-known standards such as MPEG-4, H.264/AVC and H.265/HEVC.…
Inferring Point Cloud Quality via Graph Similarity
Qi Yang, Zhan Ma, Yiling Xu +2
We propose the GraphSIM -- an objective metric to accurately predict the subjective quality of point cloud with superimposed geometry and color impairments. Motivated by the facts…
Object-Based Image Coding: A Learning-Driven Revisit
Qi Xia, Haojie Liu, Zhan Ma
The Object-Based Image Coding (OBIC) that was extensively studied about two decades ago, promised a vast application perspective for both ultra-low bitrate communication and high-l…
Intelligent Autofocus
Chengyu Wang, Qian Huang, Ming Cheng +2
We demonstrate that deep learning methods can determine the best focus position from 1-2 image samples, enabling 5-10x faster focus than traditional search-based methods. In contra…
Smart Cameras
David J. Brady, Minghao Hu, Chengyu Wang +6
We review camera architecture in the age of artificial intelligence. Modern cameras use physical components and software to capture, compress and display image data. Over the past…
Learning End-to-End Lossy Image Compression: A Benchmark
Yueyu Hu, Wenhan Yang, Zhan Ma +1
Image compression is one of the most fundamental techniques and commonly used applications in the image and video processing field. Earlier methods built a well-designed pipeline,…
Learned Video Compression via Joint Spatial-Temporal Correlation Exploration
Haojie Liu, Han shen, Lichao Huang +3
Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role i…
Neural Image Compression via Non-Local Attention Optimization and Improved Context Modeling
Tong Chen, Haojie Liu, Zhan Ma +3
This paper proposes a novel Non-Local Attention optmization and Improved Context modeling-based image compression (NLAIC) algorithm, which is built on top of the deep nerual networ…
Learned Point Cloud Geometry Compression
Jianqiang Wang, Hao Zhu, Zhan Ma +3
This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a.k.a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep…
A Dual Camera System for High Spatiotemporal Resolution Video Acquisition
Ming Cheng, Zhan Ma, M. Salman Asif +4
This paper presents a dual camera system for high spatiotemporal resolution (HSTR) video acquisition, where one camera shoots a video with high spatial resolution and low frame rat…
Compressive Sampling for Array Cameras
Xuefei Yan, David J. Brady, Jianqiang Wang +5
While design of high performance lenses and image sensors has long been the focus of camera development, the size, weight and power of image data processing components is currently…
Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications
Ming Lu, Ming Cheng, Yiling Xu +3
Networked video applications, e.g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth. In this paper, we have de…
Non-local Attention Optimized Deep Image Compression
Haojie Liu, Tong Chen, Peiyao Guo +4
This paper proposes a novel Non-Local Attention Optimized Deep Image Compression (NLAIC) framework, which is built on top of the popular variational auto-encoder (VAE) structure. O…
Extreme Image Coding via Multiscale Autoencoders With Generative Adversarial Optimization
Chao Huang, Haojie Liu, Tong Chen +2
We propose a MultiScale AutoEncoder(MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate. Our method leverages the "prior…
Gated Context Model with Embedded Priors for Deep Image Compression
Haojie Liu, Tong Chen, Peiyao Guo +2
A deep image compression scheme is proposed in this paper, offering the state-of-the-art compression efficiency, against the traditional JPEG, JPEG2000, BPG and those popular learn…
Neural Video Compression using Spatio-Temporal Priors
Haojie Liu, Tong Chen, Ming Lu +2
The pursuit of higher compression efficiency continuously drives the advances of video coding technologies. Fundamentally, we wish to find better "predictions" or "priors" that are…