B‑spline–based method for 2D animation inbetweening that preserves outline clarity and handles large motion spans; combines contour vectorization, structural matching, clustering, and quadratic trajectory prediction.
Complete reproduction and critical analysis of Simo-Serra et al.’s rough sketch simplification paper; includes Lua/Torch to Python/PyTorch migration, loss function validation, and dataset construction experiments.
Undergraduate thesis proposing a dual-LightGCN model to decompose implicit feedback into Preference and Exposure matrices, substantially reducing estimation variance and improving performance on benchmark datasets (Yahoo!R3, Coat).