50 citations · 201 across the 26 of their papers we have counts for
31 papers · 1 filter
DreamVAR: Taming Reinforced Visual Autoregressive Model for High-Fidelity Subject-Driven Image Generation
Xin Jiang, Jingwen Chen, Yehao Li +5
Recent advances in subject-driven image generation using diffusion models have attracted considerable attention for their remarkable capabilities in producing high-quality images.…
Visual Autoregressive Modeling for Instruction-Guided Image Editing
Qingyang Mao, Qi Cai, Yehao Li +5
Recent advances in diffusion models have brought remarkable visual fidelity to instruction-guided image editing. However, their global denoising process inherently entangles the ed…
HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer
Qi Cai, Jingwen Chen, Yang Chen +19
Recent advancements in image generative foundation models have prioritized quality improvements but often at the cost of increased computational complexity and inference latency. T…
Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots
Guangting Zheng, Yehao Li, Yingwei Pan +4
Autoregressive models have emerged as a powerful generative paradigm for visual generation. The current de-facto standard of next token prediction commonly operates over a single-s…
Unleashing Text-to-Image Diffusion Prior for Zero-Shot Image Captioning
Jianjie Luo, Jingwen Chen, Yehao Li +4
Recently, zero-shot image captioning has gained increasing attention, where only text data is available for training. The remarkable progress in text-to-image diffusion model prese…
Improving Text-guided Object Inpainting with Semantic Pre-inpainting
Yifu Chen, Jingwen Chen, Yingwei Pan +4
Recent years have witnessed the success of large text-to-image diffusion models and their remarkable potential to generate high-quality images. The further pursuit of enhancing the…