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XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation
Xiang Li, Kai Qiu, Hao Chen +5
Image tokenizers play a critical role in shaping the performance of subsequent generative models. Since the introduction of VQ-GAN, discrete image tokenization has undergone remark…
SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer
Hao Chen, Ze Wang, Xiang Li +7
Efficient image tokenization with high compression ratios remains a critical challenge for training generative models. We present SoftVQ-VAE, a continuous image tokenizer that leve…
ImageFolder: Autoregressive Image Generation with Folded Tokens
Xiang Li, Kai Qiu, Hao Chen +4
Image tokenizers are crucial for visual generative models, e.g., diffusion models (DMs) and autoregressive (AR) models, as they construct the latent representation for modeling. In…
Efficient Autoregressive Audio Modeling via Next-Scale Prediction
Kai Qiu, Xiang Li, Hao Chen +5
Audio generation has achieved remarkable progress with the advance of sophisticated generative models, such as diffusion models (DMs) and autoregressive (AR) models. However, due t…
ControlVAR: Exploring Controllable Visual Autoregressive Modeling
Xiang Li, Kai Qiu, Hao Chen +4
Conditional visual generation has witnessed remarkable progress with the advent of diffusion models (DMs), especially in tasks like control-to-image generation. However, challenges…
RTGen: Generating Region-Text Pairs for Open-Vocabulary Object Detection
Fangyi Chen, Han Zhang, Zhantao Yang +3
Open-vocabulary object detection (OVD) requires solid modeling of the region-semantic relationship, which could be learned from massive region-text pairs. However, such data is lim…