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cs.CV2026
Soft Tail-dropping for Adaptive Visual Tokenization
Zeyuan Chen, Kai Zhang, Zhuowen Tu +1
We present Soft Tail-dropping Adaptive Tokenizer (STAT), a 1D discrete visual tokenizer that adaptively chooses the number of output tokens per image according to its structural co…
cs.CV2025
AlignTok: Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models
Bowei Chen, Sai Bi, Hao Tan +6
In this work, we propose aligning pretrained visual encoders to serve as tokenizers for latent diffusion models in image generation. Unlike training a variational autoencoder (VAE)…
cs.CV2024
RetinaGS: Scalable Training for Dense Scene Rendering with Billion-Scale 3D Gaussians
Bingling Li, Shengyi Chen, Luchao Wang +3
In this work, we explore the possibility of training high-parameter 3D Gaussian splatting (3DGS) models on large-scale, high-resolution datasets. We design a general model parallel…