attention-based bi-prediction network versatile video coding is a M.Tech project topic for Electronics & Communication Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
attention-based bi-prediction network versatile video coding Project Details
| Abstract |
Versatile Video Coding (VVC, also called H.266) is the newest video‑compression standard. It cuts bitrates much more than the older High Efficiency Video Coding (HEVC). Sending high‑resolution video over a fast‑changing 5G network still needs better compression efficiency and stronger error resilience. This project looks at adding an attention‑based bi‑prediction network to VVC to improve inter‑prediction. The network uses deep‑learning attention to adjust motion vectors on the fly and to merge two reference frames more accurately. This lowers the amount of residual data that has to be coded. We test the system in a simulated 5G environment with different bandwidths and packet‑loss rates. The steps are: – Build the bi‑prediction
network in a deep‑learning framework. – Plug the network into a VVC‑compatible software codec. – Measure how computational load, compression efficiency (BD‑rate), and transmission robustness trade off against each other. The project supplies a clear research plan, code‑level help, and simulation instructions for evaluating neural‑network‑based video‑coding upgrades aimed at next‑generation wireless systems. We benchmark performance with standard video sequences to confirm the expected rate‑distortion gains.
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| Reference Paper |
Attention-Based Bi-Prediction Network for Versatile Video Coding (VVC) over 5G Network. |
| Domain |
Electronics & Communication Engineering |
| Sub-Domain |
Signal & Image Processing / Image & Video Processing / Video Coding |
| PDF Download |
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