From the 1 of 11 linked papers with an AI index.
11 papers
FiRE: Enhancing MLLMs with Fine-Grained Context Learning for Complex Image Retrieval
Bohan Hou, Haoqiang Lin, Xuemeng Song +4
The paper introduces an automated pipeline to create a fine-grained multimodal dataset and a two-stage fine-tuning strategy that improves multimodal large language models' ability…
Diverse-Intent Multi-Turn Fashion Image Retrieval
Mingqiang Tang, Haokun Wen, Meng Liu +3
Real-world fashion search involves interactive retrieval across multiple turns. However, existing multi-turn retrieval methods are built on a restrictive assumption that every inte…
COMBINER: Composed Image Retrieval Guided by Attribute-based Neighbor Relations
Zixu Li, Yupeng Hu, Zhiwei Chen +3
Composed Image Retrieval (CIR) represents a challenging retrieval task that targets locating specific images through multimodal inputs. Despite recent progress in CIR techniques, p…
FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning
Haokun Wen, Xuemeng Song, Xinghao Xie +3
Fashion image retrieval is a cornerstone of modern e-commerce systems. A unified framework that supports diverse query formats and search intentions is highly desired in practice.…
UniCVR: From Alignment to Reranking for Unified Zero-Shot Composed Visual Retrieval
Haokun Wen, Xuemeng Song, Haoyu Zhang +3
Composed image retrieval, multi-turn composed image retrieval, and composed video retrieval all share a common paradigm: composing the reference visual with modification text to re…
HUD: Hierarchical Uncertainty-Aware Disambiguation Network for Composed Video Retrieval
Zhiwei Chen, Yupeng Hu, Zixu Li +3
Composed Video Retrieval (CVR) is a challenging video retrieval task that utilizes multi-modal queries, consisting of a reference video and modification text, to retrieve the desir…