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Yitong Yang

4 accepted papers

2026

DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimization

ICML 2026poster

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model itself, while diffusion-based approaches can capture such consis…

Cited by 0SourceScholar
2026

FantasyStyle: Controllable Stylized Distillation for 3D Gaussian Splatting

AAAI 2026technical

The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1) multi-view inconsistency often leads to style conflicts, resulting in appearance smoothing and distortion; and (2) heavy

Cited by 0SourcePDFScholar
2026

SplitFlux: Learning to Decouple Content and Style from a Single Image

CVPR 2026

Disentangling image content and style is essential for customized image generation. Existing SDXL-based methods struggle to achieve high-quality results, while the recently proposed Flux model fails to achieve effective content-style separation due to its underexplored characteristics. To address th

Cited by 0SourcecodeScholar
2023

High-Frequency Stereo Matching Network

CVPR 2023highlight

In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it difficult to generate more detailed difference maps that take full advantage of hi…

Cited by 86SourcePDFScholar