13 citations · 42 across the 11 of their papers we have counts for
11 papers
Boosting 3D Object Detection with Semantic-Aware Multi-Branch Framework
Hao Jing, Anhong Wang, Lijun Zhao +5
In autonomous driving, LiDAR sensors are vital for acquiring 3D point clouds, providing reliable geometric information. However, traditional sampling methods of preprocessing often…
Deep Optimized Multiple Description Image Coding via Scalar Quantization Learning
Lijun Zhao, Huihui Bai, Anhong Wang +1
In this paper, we introduce a deep multiple description coding (MDC) framework optimized by minimizing multiple description (MD) compressive loss. First, MD multi-scale-dilated enc…
Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation
Lijun Zhao, Jinjing Zhang, Fan Zhang +3
Most deep image smoothing operators are always trained repetitively when different explicit structure-texture pairs are employed as label images for each algorithm configured with…
Deep Multiple Description Coding by Learning Scalar Quantization
Lijun Zhao, Huihui Bai, Anhong Wang +1
In this paper, we propose a deep multiple description coding framework, whose quantizers are adaptively learned via the minimization of multiple description compressive loss. First…
Virtual Codec Supervised Re-Sampling Network for Image Compression
Lijun Zhao, Huihui Bai, Anhong Wang +1
In this paper, we propose an image re-sampling compression method by learning virtual codec network (VCN) to resolve the non-differentiable problem of quantization function for ima…
Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks
Lijun Zhao, Huihui Bai, Feng Li +2
In this paper, we propose an end-to-end mixed-resolution image compression framework with convolutional neural networks. Firstly, given one input image, feature description neural…
Learning a Virtual Codec Based on Deep Convolutional Neural Network to Compress Image
Lijun Zhao, Huihui Bai, Anhong Wang +1
Although deep convolutional neural network has been proved to efficiently eliminate coding artifacts caused by the coarse quantization of traditional codec, it's difficult to train…
Multiple Description Convolutional Neural Networks for Image Compression
Lijun Zhao, Huihui Bai, Anhong Wang +1
Multiple description coding (MDC) is able to stably transmit the signal in the un-reliable and non-prioritized networks, which has been broadly studied for several decades. However…
Cascaded Reconstruction Network for Compressive image sensing
Yahan Wang, Huihui Bai, Lijun Zhao +1
The theory of compressed sensing (CS) has been successfully applied to image compression in the past few years, whose traditional iterative reconstruction algorithm is time-consumi…
Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network
Lijun Zhao, Huihui Bai, Jie Liang +3
Recently, Generative Adversarial Network (GAN) has been found wide applications in style transfer, image-to-image translation and image super-resolution. In this paper, a color-dep…
Local Activity-tuned Image Filtering for Noise Removal and Image Smoothing
Lijun Zhao, Jie Liang, Huihui Bai +3
In this paper, two local activity-tuned filtering frameworks are proposed for noise removal and image smoothing, where the local activity measurement is given by the clipped and no…