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cs.CV2026
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…
cs.CV2025★ 29 cited
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…
cs.CV2024
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…