3 papers
cs.CV2026
Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion
Yiran Qiao, Yiren Lu, Yunlai Zhou +5
3D asset generation plays a pivotal role in fields such as gaming and virtual reality, enabling the rapid synthesis of high-fidelity 3D objects from a single or multiple images. Bu…
cs.CV2025
Stroke2Sketch: Harnessing Stroke Attributes for Training-Free Sketch Generation
Rui Yang, Huining Li, Yiyi Long +2
Generating sketches guided by reference styles requires precise transfer of stroke attributes, such as line thickness, deformation, and texture sparsity, while preserving semantic…
cs.CV2025
MixSA: Training-free Reference-based Sketch Extraction via Mixture-of-Self-Attention
Rui Yang, Xiaojun Wu, Shengfeng He
Current sketch extraction methods either require extensive training or fail to capture a wide range of artistic styles, limiting their practical applicability and versatility. We i…