Autonomous Fashion Outfit Composition via Unified Aesthetic Foresight Model
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
The Flow has not summarised this story yet — read it at arXiv Machine Learning.
arXiv:2608. 13888v1 Announce Type: new Abstract: The task of synthesizing stylistically coherent fashion outfits from massive item libraries, known as fashion outfit generation, remains a non-trivial challenge, primarily due to the non-monotonic and implicit nature of aesthetic compatibility, coupled with the exponentially large combinatorial search space.
The task of synthesizing stylistically coherent fashion outfits from massive item libraries, known as fashion outfit generation, remains a non-trivial challenge, primarily due to the non-monotonic and implicit nature of aesthetic compatibility, coupled with the exponentially large combinatorial search space. In this paper, we formalize this task as Constrained Ensemble Generation (CEG) and model it as a finite-horizon deterministic Markov Decision Process.
arXiv:2608.29804v1 Announce Type: new Abstract: Virtual try-on (VTON) requires not only realistic generation but also faithful preservation of garment characteristics. However, existing evaluation me...
RAGDiffusion++ advances garment generation by addressing the high‑frequency texture gap that previous retrieval‑augmented models left unresolved. The approach introduces a dual‑image FLUX architecture trained on a large, complex garment dataset, coupled with a new attribute‑aware reward model that guides reinforcement learning to favor realistic high‑frequency patterns. An adversarial‑regularized RL strategy (AR‑GRPO) further prevents artifact exploitation, ensuring the model samples authentic, detailed garment textures.
arXiv:2608.23302v1 Announce Type: new Abstract: Fashion complementary image generation (CIG) aims to create garments that stylistically match a seed item based on user intent, making it a natural mul...
Fashion complementary image generation (CIG) aims to create garments that stylistically match a seed item based on user intent, making it a natural multimodal grounding problem where models must inter...