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Found 18 papers, 5 papers with code
Reduced Reference Quality Assessment for Point Cloud Compression
Specifically, we use the attribute and geometry quantization steps of different compression methods (i. e., V-PCC, G-PCC and AVS) to infer the point cloud quality, assuming that the point clouds have no other distortions before compression.
GPA-Net:No-Reference Point Cloud Quality Assessment with Multi-task Graph Convolutional Network
To extract effective features for PCQA, we propose a new graph convolution kernel, i. e., GPAConv, which attentively captures the perturbation of structure and texture.
Evaluating Point Cloud Quality via Transformational Complexity
Full-reference point cloud quality assessment (FR-PCQA) aims to infer the quality of distorted point clouds with available references.
Point Cloud Quality Assessment using 3D Saliency Maps
Considering the importance of saliency detection in quality assessment, we propose an effective full-reference PCQA metric which makes the first attempt to utilize the saliency information to facilitate quality prediction, called point cloud quality assessment using 3D saliency maps (PQSM).
Multiscale Latent-Guided Entropy Model for LiDAR Point Cloud Compression
Besides, we propose a residual coding framework for the compression of the latent variable, which explores the spatial correlation of each layer by progressive downsampling, and model the corresponding residual with a fully-factorized entropy model.
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System
We utilize a disparity network to transfer spatiotemporal information across views even in large disparity scenes, based on which, we propose disparity-guided flow-based warping for LSR-HFR view and complementary warping for HSR-LFR view.
D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion Prediction
This paper proposes a novel 3D sparse convolution-based Deep Dynamic Point Cloud Compression (D-DPCC) network to compensate and compress the DPC geometry with 3D motion estimation and motion compensation in the feature space.
4DAC: Learning Attribute Compression for Dynamic Point Clouds
In addition, we also propose a deep conditional entropy model to estimate the probability distribution of the transformed coefficients, by incorporating temporal context from consecutive point clouds and the motion estimation/compensation modules.
3DAC: Learning Attribute Compression for Point Clouds
Finally, the estimated probabilities are used to further compress these transform coefficients to a final attributes bitstream.
No-Reference Point Cloud Quality Assessment via Domain Adaptation
We present a novel no-reference quality assessment metric, the image transferred point cloud quality assessment (IT-PCQA), for 3D point clouds.
Which One is Better: Assessing Objective Metrics for Point Cloud Compression
Point cloud compression (PCC) has made remarkable achievement in recent years.
ANT: Learning Accurate Network Throughput for Better Adaptive Video Streaming
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 mainly leveraged for future network bandwidth prediction.
MPED: Quantifying Point Cloud Distortion based on Multiscale Potential Energy Discrepancy
In this paper, we propose a new distortion quantification method for point clouds, the multiscale potential energy discrepancy (MPED).
Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference Metric
Full-reference (FR) point cloud quality assessment (PCQA) has achieved impressive progress in recent years.
Blind Image Quality Assessment
Point Cloud Quality Assessment
Inferring Point Cloud Quality via Graph Similarity
We propose the GraphSIM -- an objective metric to accurately predict the subjective quality of point cloud with superimposed geometry and color impairments.
A Dual Camera System for High Spatiotemporal Resolution Video Acquisition
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.
Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications
Networked video applications, e. g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth.
IoT Security: An End-to-End View and Case Study
The work in this paper raises the alarm again for the IoT device manufacturers to better secure their products in order to prevent malware attacks like Mirai.
Cryptography and Security
