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20222025
most citedAutoCAD: Automatically Generating Counterfactuals for Mitigating Shortcut Learning

3 citations · 3 across the 7 of their papers we have counts for

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cs.CV2025

From Imitation to Innovation: The Emergence of AI Unique Artistic Styles and the Challenge of Copyright Protection

Zexi Jia, Chuanwei Huang, Yeshuang Zhu +6

Current legal frameworks consider AI-generated works eligible for copyright protection when they meet originality requirements and involve substantial human intellectual input. How…

cs.CV2025

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets

Zexi Jia, Chuanwei Huang, Hongyan Fei +6

Vision-language models (VLMs) often struggle with compositional reasoning due to insufficient high-quality image-text data. To tackle this challenge, we propose a novel block-based…

cs.CV2025

Control-CLIP: Decoupling Category and Style Guidance in CLIP for Specific-Domain Generation

Zexi Jia, Chuanwei Huang, Hongyan Fei +4

Text-to-image diffusion models have shown remarkable capabilities of generating high-quality images closely aligned with textual inputs. However, the effectiveness of text guidance…

cs.CV2025

Semantic to Structure: Learning Structural Representations for Infringement Detection

Chuanwei Huang, Zexi Jia, Hongyan Fei +4

Structural information in images is crucial for aesthetic assessment, and it is widely recognized in the artistic field that imitating the structure of other works significantly in…

cs.CV2024

ILDiff: Generate Transparent Animated Stickers by Implicit Layout Distillation

Ting Zhang, Zhiqiang Yuan, Yeshuang Zhu +1

High-quality animated stickers usually contain transparent channels, which are often ignored by current video generation models. To generate fine-grained animated transparency chan…