no code implementations • 11 Apr 2022 • Haojie Liu, Daoxun Xia, Wei Jiang, Chao Xu
In order to mitigate the impact of large modality discrepancy existing in heterogeneous images, previous methods attempt to apply generative adversarial network (GAN) to generate the modality-consisitent data.
no code implementations • 8 Dec 2021 • Xudong Huang, Chunyu Lin, Haojie Liu, Lang Nie, Yao Zhao
LiDAR sensors are widely used in autonomous driving due to the reliable 3D spatial information.
no code implementations • 5 Aug 2021 • Haojie Liu, Ming Lu, Zhiqi Chen, Xun Cao, Zhan Ma, Yao Wang
We further design a one-to-many decoder pipeline to generate multiple predictions from the CSTR, including vector-based resampling, adaptive kernel-based resampling, compensation mode selection maps and texture enhancements, and combines them adaptively to achieve more accurate inter prediction.
no code implementations • 4 Apr 2021 • Zhiqi Chen, Ran Wang, Haojie Liu, Yao Wang
At the finest scale, the two warped frames are adaptively blended to generate the middle frame.
no code implementations • 24 Feb 2021 • Haojie Liu, Shun Ma, Daoxun Xia, Shaozi Li
In feature-level, we improve the conventional two-stream network through balancing the number of specific and sharable convolutional blocks, which preserve the spatial structure information of features.
no code implementations • 9 Jul 2020 • Haojie Liu, Ming Lu, Zhan Ma, Fan Wang, Zhihuang Xie, Xun Cao, Yao Wang
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.
no code implementations • 20 Jun 2020 • Haojie Liu, Kang Liao, Chunyu Lin, Yao Zhao, Yulan Guo
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 and LiDAR.
no code implementations • 18 Mar 2020 • 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-level semantical content understanding, but it had rarely been used due to the inefficient compact representation of object with arbitrary shape.
no code implementations • 13 Dec 2019 • Haojie Liu, Han Shen, Lichao Huang, Ming Lu, Tong Chen, Zhan Ma
Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency.
1 code implementation • 11 Oct 2019 • Tong Chen, Haojie Liu, Zhan Ma, Qiu Shen, Xun Cao, Yao Wang
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 network (DNN)-based variational auto-encoder (VAE) structure.
no code implementations • 28 Sep 2019 • Ming Cheng, Zhan Ma, M. Salman Asif, Yiling Xu, Haojie Liu, Wenbo Bao, Jun Sun
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 rate (HSR-LFR) and another one captures a low spatial resolution and high frame rate (LSR-HFR) video.
2 code implementations • 26 Sep 2019 • Jianqiang Wang, Hao Zhu, Zhan Ma, Tong Chen, Haojie Liu, Qiu Shen
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 neural networks (DNN) based variational autoencoders (VAE).
no code implementations • 16 Sep 2019 • Haojie Liu, Kang Liao, Chunyu Lin, Yao Zhao, Yulan Guo
In this paper, we propose a novel Pseudo-LiDAR interpolation network (PLIN) to increase the frequency of LiDAR sensors.
no code implementations • 22 Apr 2019 • Haojie Liu, Tong Chen, Peiyao Guo, Qiu Shen, Xun Cao, Yao Wang, Zhan Ma
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.
no code implementations • 8 Apr 2019 • Chao Huang, Haojie Liu, Tong Chen, Qiu Shen, Zhan Ma
We propose a MultiScale AutoEncoder(MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate.
no code implementations • 27 Feb 2019 • Haojie Liu, Tong Chen, Peiyao Guo, Qiu Shen, Zhan Ma
Besides, a field study on perceptual quality is also given via a dedicated subjective assessment, to compare the efficiency of our proposed methods and other conventional image compression methods.
1 code implementation • 5 Jun 2018 • Haojie Liu, Tong Chen, Qiu Shen, Tao Yue, Zhan Ma
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-scale structural similarity (MS-SSIM), at the same bit rate.