AI BriefingMulti-Platform Learned Video Codec MLVC Unveiled
Key point
It proposes MLVC, a learned video codec capable of real-world deployment by solving the numerical inconsistency problem between NPUs.
Details
Existing learned video codecs (Neural Codec) offer advantages in computational efficiency and power consumption, but the cross-platform compatibility issue—where the entropy model breaks down due to numerical inconsistencies between different NPUs (e.g., Apple vs Intel)—has been pointed out as a key limitation.
MLVC introduces the following approach to solve this:
- By explicitly passing the scale parameters of the entropy model through a Hyperprior, it is designed to enable decoding even when NPUs do not match completely at the bit level.
- This bypasses hardware and toolchain standardization issues (rounding modes, accumulation data types, etc.).
Actual test results demonstrated that encoding and decoding are possible at a speed of about 100 FPS at 360p/540p resolution on a consumer NPU, increasing the possibility of real-world service deployment.
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