7 papers
RAVA: Retrieval-Augmented Viewpoint Alignment for Subject-Driven Image Generation
Qiwei Yan, Zhiqiang Yuan, Chongyang Li +4
Reference-driven image generation has made rapid progress on identity preservation, but reliable viewpoint control across different subjects remains poorly understood. The difficul…
Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants
Chongyang Li, Zhiqiang Yuan, Hanbo Bi +2
Approximately 283 million people worldwide live with visual impairments, motivating increasing research into leveraging Visual Language Models (VLMs) to develop effective walking a…
RDTF: Resource-efficient Dual-mask Training Framework for Multi-frame Animated Sticker Generation
Zhiqiang Yuan, Ting Zhang, Peixiang Luo +5
Recently, significant advancements have been achieved in video generation technology, but applying it to resource-constrained downstream tasks like multi-frame animated sticker gen…
F2RVLM: Boosting Fine-grained Fragment Retrieval for Multi-Modal Long-form Dialogue with Vision Language Model
Hanbo Bi, Zhiqiang Yuan, Zexi Jia +6
Traditional dialogue retrieval aims to select the most appropriate utterance or image from recent dialogue history. However, they often fail to meet users' actual needs for revisit…
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…
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…