8 papers
AIBench: Evaluating Visual-Logical Consistency in Academic Illustration Generation
Zhaohe Liao, Kaixun Jiang, Zhihang Liu +11
Although image generation has boosted various applications via its rapid evolution, whether the state-of-the-art models are able to produce ready-to-use academic illustrations for…
MACRO: Advancing Multi-Reference Image Generation with Structured Long-Context Data
Zhekai Chen, Yuqing Wang, Manyuan Zhang +1
Generating images conditioned on multiple visual references is critical for real-world applications such as multi-subject composition, narrative illustration, and novel view synthe…
Cubic Discrete Diffusion: Discrete Visual Generation on High-Dimensional Representation Tokens
Yuqing Wang, Chuofan Ma, Zhijie Lin +7
Visual generation with discrete tokens has gained significant attention as it enables a unified token prediction paradigm shared with language models, promising seamless multimodal…
Bridging Continuous and Discrete Tokens for Autoregressive Visual Generation
Yuqing Wang, Zhijie Lin, Yao Teng +4
Autoregressive visual generation models typically rely on tokenizers to compress images into tokens that can be predicted sequentially. A fundamental dilemma exists in token repres…
GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generation
Tianwei Xiong, Jun Hao Liew, Zilong Huang +2
In autoregressive (AR) image generation, visual tokenizers compress images into compact discrete latent tokens, enabling efficient training of downstream autoregressive models for…
Parallelized Autoregressive Visual Generation
Yuqing Wang, Shuhuai Ren, Zhijie Lin +6
Autoregressive models have emerged as a powerful approach for visual generation but suffer from slow inference speed due to their sequential token-by-token prediction process. In t…