10 papers
SAIL: Perceptual Quality-Aware Rate Control for Cloud Gaming
Houde Qian, Chenglei Wu, Jiaxing Zhang +8
Cloud gaming streams cloud-rendered frames under strict motion-to-photon latency, yet its at-scale viability is increasingly constrained by bandwidth cost: in our study of the T cl…
A Mamba-based Perceptual Loss Function for Learning-based UGC Transcoding
Zihao Qi, Chen Feng, Fan Zhang +3
In user-generated content (UGC) transcoding, source videos typically suffer various degradations due to prior compression, editing, or suboptimal capture conditions. Consequently,…
Instance Data Condensation for Image Super-Resolution
Tianhao Peng, Ho Man Kwan, Yuxuan Jiang +5
Deep learning based Image Super-Resolution (ISR) relies on large training datasets to optimize model generalization; this requires substantial computational and storage resources d…
Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-relevance Degradation Description
Yipeng Liu, Qi Yang, Yujie Zhang +4
The visual quality of point clouds plays a crucial role in the development and broadcasting of immersive media. Therefore, investigating point cloud quality assessment (PCQA) is in…
GeodesicPSIM: Predicting the Quality of Static Mesh with Texture Map via Geodesic Patch Similarity
Qi Yang, Joel Jung, Xiaozhong Xu +1
Static meshes with texture maps have attracted considerable attention in both industrial manufacturing and academic research, leading to an urgent requirement for effective and rob…
Transferable Learned Image Compression-Resistant Adversarial Perturbations
Yang Sui, Zhuohang Li, Ding Ding +4
Adversarial attacks can readily disrupt the image classification system, revealing the vulnerability of DNN-based recognition tasks. While existing adversarial perturbations are pr…