StableVQ: Turning Vector-Quantized Tokenizer Training Stability from a Fragile Outcome into a Guaranteed Property
The work proposes StableVQ, three parameter-free components — Dynamic STE, Region VQ Loss, and Decoupled Schedule — that disentangle Encoder–Decoder and Codebook training so each module can fulfill its own responsibility independently, consistently improving training stability, codebook utilization, and reconstruction quality on ImageNet across diverse codebook sizes and initialization settings.