8 papers
Adaptive 1D Video Diffusion Autoencoder
Yao Teng, Minxuan Lin, Xian Liu +3
Recent video generation models largely rely on video autoencoders that compress pixel-space videos into latent representations. However, existing video autoencoders suffer from thr…
SJD++: Improved Speculative Jacobi Decoding for Training-free Acceleration of Discrete Auto-regressive Text-to-Image Generation
Yao Teng, Zhihuan Jiang, Han Shi +6
Large autoregressive models can generate high-quality, high-resolution images but suffer from slow generation speed, because these models require hundreds to thousands of sequentia…
Speculative Jacobi-Denoising Decoding for Accelerating Autoregressive Text-to-image Generation
Yao Teng, Fuyun Wang, Xian Liu +7
As a new paradigm of visual content generation, autoregressive text-to-image models suffer from slow inference due to their sequential token-by-token decoding process, often requir…
T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generation
Kaiyue Sun, Rongyao Fang, Chengqi Duan +2
We propose T2I-ReasonBench, a benchmark evaluating reasoning capabilities of text-to-image (T2I) models. It consists of four dimensions: Idiom Interpretation, Textual Image Design,…
HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation
Hermann Kumbong, Xian Liu, Tsung-Yi Lin +6
Visual Auto-Regressive modeling (VAR) has shown promise in bridging the speed and quality gap between autoregressive image models and diffusion models. VAR reformulates autoregress…
Personalized Text-to-Image Generation with Auto-Regressive Models
Kaiyue Sun, Xian Liu, Yao Teng +1
Personalized image synthesis has emerged as a pivotal application in text-to-image generation, enabling the creation of images featuring specific subjects in diverse contexts. Whil…