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Chang Ge

2 accepted papers

2026

Easy2Hard: From Partially to Fully Unmatched Modalities as Negative Samples in Contrastive Learning

CVPR 2026

Contrastive learning is widely used for generating multimodal data representations by aligning embeddings of different modalities of the same data samples. This alignment is achieved through a loss function that treats matched and unmatched modality pairs as positive and negative samples within a da

Cited by 0SourcecodeScholar
2026

FontCrafter: High-Fidelity Element-Driven Artistic Font Creation with Visual In-Context Generation

CVPR 2026

Artistic font generation aims to synthesize stylized glyphs based on a reference style. However, existing approaches suffer from limited style diversity and coarse control. In this work, we explore the potential of element-driven artistic font generation. Elements are the fundamental visual units of

Cited by 0SourceScholar