YuhangMa — accepted AI-conference papers

2026

RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition

Binhao Wang, Shihao Zhao, Bo Cheng, Qiuyu Ji, YuhangMa, Liebucha Wu +3

ICML 2026poster

Recent diffusion-based approaches have made substantial progress in image layer decomposition. However, accurately decomposing complex natural images remains challenging due to difficulties in occlusion completion, robust layer disentanglement, and precise foreground boundaries. Moreover, the scarci…

Cited by 0 Source ↗Scholar ↗

2024

HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generation

Bocheng, YuhangMa, wuliebucha, Shanyuan Liu, Ao Ma, Xiaoyu Wu +2

NeurIPS 2024poster

The task of layout-to-image generation involves synthesizing images based on the captions of objects and their spatial positions. Existing methods still struggle in complex layout generation, where common bad cases include object missing, inconsistent lighting, conflicting view angles, etc. To effec…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗