AI RESEARCH
TC-AE: Unlocking Token Capacity for Deep Compression Autoencoders
arXiv CS.CV
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ArXi:2604.07340v1 Announce Type: new We propose TC-AE, a ViT-based architecture for deep compression autoencoders. Existing methods commonly increase the channel number of latent representations to maintain reconstruction quality under high compression ratios. However, this strategy often leads to latent representation collapse, which degrades generative performance. Instead of relying on increasingly complex architectures or multi-stage