Dec 2025· IEEE International Symposium on Multimedia· pp. 116-123· 2 citations· 30 references
Computer ScienceEngineering
TL;DR
This work designs a system that downsamples point cloud content at the origin server and applies partial encryption at the client, and decrypted and upscaled using an ML-based super-resolution model, which effectively reconstructs the original full-resolution point clouds with minimal error and modest inference time.
Abstract
Immersive formats such as $\mathbf{3 6 0}^{{\circ}}$ and 6DoF point cloud videos require high bandwidth and low latency, posing challenges for real-time AR/VR streaming. This work focuses on reducing bandwidth consumption and encryption/decryption delay, two key contributors to overall latency. We design a system that downsamples point cloud content at the origin server and applies partial encryption. At the client, the content is decrypted and upscaled using an ML-based super-resolution model. Our evaluation demonstrates a nearly linear reduction in bandwidth/latency, and encryption/decryption overhead with lower downsampling resolutions, while the super-resolution model effectively reconstructs the original full-resolution point clouds with minimal error and modest inference time.
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MIT News · Artificial Intelligence· news.mit.eduNov 6, 2026
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
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