Hongliang Yang — accepted AI-conference papers

2026

SCORE: Semantic Collage by Optimizing Rendered Elements

Zefan Shao, Jin Zhou, Hongliang Yang, Pengfei Xu

AAAI 2026technical

Collage is a powerful medium for visual expression, traditionally demanding significant artistic expertise and manual effort. Existing methods often struggle with a trade-off between semantic expression and the visual fidelity of the constituent images. To address this, we introduce SCORE (Semantic

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2026

StrokeFusion: Vector Sketch Generation via Joint Stroke-UDF Encoding and Latent Sequence Diffusion

Jin Zhou, Yi Zhou, Hongliang Yang, Pengfei Xu, Hui Huang

AAAI 2026technical

In the field of sketch generation, raster-format trained models often produce non-stroke artifacts, while vector-format trained models typically lack a holistic understanding of sketches, leading to compromised recognizability. Moreover, existing methods struggle to extract common features from simi

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