29 citations · 29 across the 4 of their papers we have counts for
6 papers
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…
Dual Knowledge-Enhanced Two-Stage Reasoner for Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Haokun Wen +3
Textual response generation is pivotal for multimodal \mbox{task-oriented} dialog systems, which aims to generate proper textual responses based on the multimodal context. While ex…
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…
A Comprehensive Survey on Composed Image Retrieval
Xuemeng Song, Haoqiang Lin, Haokun Wen +3
Composed Image Retrieval (CIR) is an emerging yet challenging task that allows users to search for target images using a multimodal query, comprising a reference image and a modifi…