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3SGen: Unified Subject, Style, and Structure-Driven Image Generation with Adaptive Task-specific Memory
Xinyang Song, Libin Wang, Weining Wang +6
Recent image generation approaches often address subject, style, and structure-driven conditioning in isolation, leading to feature entanglement and limited task transferability. I…
Ming-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer
Ziyuan Huang, DanDan Zheng, Cheng Zou +13
Visual tokenization remains a core challenge in unifying visual understanding and generation within the autoregressive paradigm. Existing methods typically employ tokenizers in dis…
Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation
Inclusion AI, :, Bowen Ma +73
We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…
UniAlignment: Semantic Alignment for Unified Image Generation, Understanding, Manipulation and Perception
Xinyang Song, Libin Wang, Weining Wang +5
The remarkable success of diffusion models in text-to-image generation has sparked growing interest in expanding their capabilities to a variety of multi-modal tasks, including ima…
Reversing Flow for Image Restoration
Haina Qin, Wenyang Luo, Libin Wang +5
Image restoration aims to recover high-quality (HQ) images from degraded low-quality (LQ) ones by reversing the effects of degradation. Existing generative models for image restora…
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
Wenyang Luo, Haina Qin, Zewen Chen +6
Image restoration tasks like deblurring, denoising, and dehazing usually need distinct models for each degradation type, restricting their generalization in real-world scenarios wi…