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Found 16 papers, 3 papers with code
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i. e., Kuaishou/Kwai Platform.
Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment
Furthermore, in the model fine-tuning stage, we propose a semantic-guided multi-view fusion module to effectively integrate the features of projected images from multiple perspectives.
Transferable Learned Image Compression-Resistant Adversarial Perturbations
Adversarial attacks can readily disrupt the image classification system, revealing the vulnerability of DNN-based recognition tasks.
Full-reference Video Quality Assessment for User Generated Content Transcoding
In this work, we observe that existing full-/no-reference quality metrics fail to accurately predict the perceptual quality difference between transcoded UGC content and the corresponding unpristine references.
Corner-to-Center Long-range Context Model for Efficient Learned Image Compression
To tackle this issue, we conduct an in-depth analysis of the performance degradation observed in existing parallel context models, focusing on two aspects: the Quantity and Quality of information utilized for context prediction and decoding.
SJTU-TMQA: A quality assessment database for static mesh with texture map
However, little research has been done on the quality assessment of textured meshes, which hinders the development of quality-oriented applications, such as mesh compression and enhancement.
GeodesicPSIM: Predicting the Quality of Static Mesh with Texture Map via Geodesic Patch Similarity
A two-step patch cropping algorithm and a patch texture mapping module refine the size of 1-hop geodesic patches and build the relationship between the mesh geometry and color information, resulting in the generation of 1-hop textured geodesic patches.
TSMD: A Database for Static Color Mesh Quality Assessment Study
Static meshes with texture map are widely used in modern industrial and manufacturing sectors, attracting considerable attention in the mesh compression community due to its huge amount of data.
TDMD: A Database for Dynamic Color Mesh Subjective and Objective Quality Explorations
Dynamic colored meshes (DCM) are widely used in various applications; however, these meshes may undergo different processes, such as compression or transmission, which can distort them and degrade their quality.
Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-relevance Degradation Description
Second, to reduce the significant domain discrepancy, we establish an intermediate domain, the description domain, based on insights from subjective experiments, by considering the domain relevance among samples located in the perception domain and learning a structured latent space.
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations
Learned Image Compression (LIC) has recently become the trending technique for image transmission due to its notable performance.
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.
TCDM: Transformational Complexity Based Distortion Metric for Perceptual Point Cloud Quality Assessment
The goal of objective point cloud quality assessment (PCQA) research is to develop quantitative metrics that measure point cloud quality in a perceptually consistent manner.
Enhancing HDR Video Compression through CNN-based Effective Bit Depth Adaptation
In this work, we modify the MFRNet network architecture to enable multiple frame processing, and the new network, multi-frame MFRNet, has been integrated into the EBDA framework using two Versatile Video Coding (VVC) host codecs: VTM 16. 2 and the Fraunhofer Versatile Video Encoder (VVenC 1. 4. 0).
Recent Standard Development Activities on Video Coding for Machines
Specifically, we will first provide an overview of the MPEG VCM group including use cases, requirements, processing pipelines, plan for potential VCM standards, followed by the evaluation framework including machine-vision tasks, dataset, evaluation metrics, and anchor generation.
Tencent Video Dataset (TVD): A Video Dataset for Learning-based Visual Data Compression and Analysis
Learning-based visual data compression and analysis have attracted great interest from both academia and industry recently.
