A pretrained VAE can be converted into a high-compression VQ-VAE by freezing it and training only a multi-group quantizer plus a post rectifier, cutting training cost by over two orders of magnitude while keeping rFID at 1.06 on ImageNet.
Sequential modeling enables scalable learning for large vision models
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Quantize-then-Rectify: Efficient VQ-VAE Training
A pretrained VAE can be converted into a high-compression VQ-VAE by freezing it and training only a multi-group quantizer plus a post rectifier, cutting training cost by over two orders of magnitude while keeping rFID at 1.06 on ImageNet.