34 citations · 67 across the 13 of their papers we have counts for
13 papers
FPPN: Future Pseudo-LiDAR Frame Prediction for Autonomous Driving
Xudong Huang, Chunyu Lin, Haojie Liu +2
LiDAR sensors are widely used in autonomous driving due to the reliable 3D spatial information. However, the data of LiDAR is sparse and the frequency of LiDAR is lower than that o…
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…
PDWN: Pyramid Deformable Warping Network for Video Interpolation
Zhiqi Chen, Ran Wang, Haojie Liu +1
Video interpolation aims to generate a non-existent intermediate frame given the past and future frames. Many state-of-the-art methods achieve promising results by estimating the o…
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.…
Pseudo-LiDAR Point Cloud Interpolation Based on 3D Motion Representation and Spatial Supervision
Haojie Liu, Kang Liao, Chunyu Lin +2
Pseudo-LiDAR point cloud interpolation is a novel and challenging task in the field of autonomous driving, which aims to address the frequency mismatching problem between camera an…
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…
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…
PLIN: A Network for Pseudo-LiDAR Point Cloud Interpolation
Haojie Liu, Kang Liao, Chunyu Lin +2
LiDAR sensors can provide dependable 3D spatial information at a low frequency (around 10Hz) and have been widely applied in the field of autonomous driving and UAV. However, the c…
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…
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…
Deep Image Compression via End-to-End Learning
Haojie Liu, Tong Chen, Qiu Shen +2
We present a lossy image compression method based on deep convolutional neural networks (CNNs), which outperforms the existing BPG, WebP, JPEG2000 and JPEG as measured via multi-sc…