Shining Yourself: High-Fidelity Ornaments Virtual Try-on with Diffusion Model
While virtual try-on for clothes and shoes with diffusion models has gained attraction, virtual try-on for ornaments, such as bracelets, rings, earrings, and necklaces, remains largely unexplored. Due to the intricate tiny patterns and repeated geometric sub-structures in most ornaments, it is much more difficult to guarantee identity and appearance consistency under large pose and scale variances between ornaments and models. This paper proposes the task of virtual try-on for ornaments and presents a method to improve the geometric and appearance preservation of ornament virtual try-ons. Specifically, we estimate an accurate wearing mask to improve the alignments between ornaments and models in an iterative scheme alongside the denoising process. To preserve structure details, we further regularize attention layers to map the reference ornament mask to the wearing mask in an implicit way. Experimental results demonstrate that our method successfully wears ornaments from reference images onto target models, handling substantial differences in scale and pose while preserving identity and achieving realistic visual effects.
Code (0)
등록된 구현이 없습니다.
Tasks
DenoisingVirtual Try-onMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Historical Printed Ornaments: Dataset and Tasks
This paper aims to develop the study of historical printed ornaments with modern unsupervised computer vision. We highlight three complex tasks that are of critical interest to book historians: clustering, element discov…
DiversityA Stochastic Temporal Model of Polyphonic MIDI Performance with Ornaments
We study indeterminacies in realization of ornaments and how they can be incorporated in a stochastic performance model applicable for music information processing such as score-performance matching. We point out the imp…
EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Transformers
Current generative video models excel at producing novel content from text and image prompts, but leave a critical gap in editing existing pre-recorded videos, where minor alterations to the spoken script require preserv…
UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections
We present UP2You, the first tuning-free solution for reconstructing high-fidelity 3D clothed portraits from extremely unconstrained in-the-wild 2D photos. Unlike previous approaches that require "clean" inputs (e.g., fu…
3D ReconstructionVirtual Try-onRecognizing Ornaments in Vocal Indian Art Music with Active Annotation
Ornamentations, embellishments, or microtonal inflections are essential to melodic expression across many musical traditions, adding depth, nuance, and emotional impact to performances. Recognizing ornamentations in sing…
ChunkingGenre classificationSinger IdentificationTime Series Analysis