53 citations · 141 across the 14 of their papers we have counts for
11 papers · 1 filter
FiRE: Enhancing MLLMs with Fine-Grained Context Learning for Complex Image Retrieval
Bohan Hou, Haoqiang Lin, Xuemeng Song +4
Due to their strong generalizable multimodal processing and reasoning capabilities, Multimodal Large Language Models (MLLMs) have demonstrated significant potential as universal im…
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…
Spatial Understanding from Videos: Structured Prompts Meet Simulation Data
Haoyu Zhang, Meng Liu, Zaijing Li +4
Visual-spatial understanding, the ability to infer object relationships and layouts from visual input, is fundamental to downstream tasks such as robotic navigation and embodied in…
FineCIR: Explicit Parsing of Fine-Grained Modification Semantics for Composed Image Retrieval
Zixu Li, Zhiheng Fu, Yupeng Hu +3
Composed Image Retrieval (CIR) facilitates image retrieval through a multimodal query consisting of a reference image and modification text. The reference image defines the retriev…
Fine-grained Textual Inversion Network for Zero-Shot Composed Image Retrieval
Haoqiang Lin, Haokun Wen, Xuemeng Song +3
Composed Image Retrieval (CIR) allows users to search target images with a multimodal query, comprising a reference image and a modification text that describes the user's modifica…
Pseudo-triplet Guided Few-shot Composed Image Retrieval
Bohan Hou, Haoqiang Lin, Haokun Wen +3
Composed Image Retrieval (CIR) is a challenging task that aims to retrieve the target image with a multimodal query, i.e., a reference image, and its complementary modification tex…
Interactive Garment Recommendation with User in the Loop
Federico Becattini, Xiaolin Chen, Andrea Puccia +4
Recommending fashion items often leverages rich user profiles and makes targeted suggestions based on past history and previous purchases. In this paper, we work under the assumpti…