Innovative and technical principles of QVC technology
Deeptrain's Quantized Video Compression (QVC) is fundamentally different from traditional coding standards such as H.264/AV1, mainly in the following three dimensions:
- Different design objectives: Traditional compression is optimized for human vision, QVC is designed for AI model recognition, preserving the feature tensor rather than visual fidelity
- Technology realization approach: Through neural network quantization technology, the video frame features are mapped to a low-dimensional space, with a typical compression ratio of up to 1:50 still maintaining the AI recognition accuracy of 90%+.
- Data flow optimization: The compressed data format directly interfaces with mainstream AI frameworks (e.g. PyTorch/TensorFlow), eliminating the arithmetic consumption of decoding.
Actual tests showed that 10 minutes of 1080p video was processed by QVC:
Storage usage from 1.2GB → 24MB
3X faster AI content extraction
Particularly suitable for MLOps scenarios that require long-term storage of training data
This answer comes from the articleDeeptrain: converting video content into large model retrievable informationThe
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