3 citations · 4 across the 17 of their papers we have counts for
5 papers · 2 filters
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval?
Yuxin Chen, Zongyang Ma, Ziqi Zhang +7
Dominant dual-encoder models enable efficient image-text retrieval but suffer from limited accuracy while the cross-encoder models offer higher accuracy at the expense of efficienc…
EA-VTR: Event-Aware Video-Text Retrieval
Zongyang Ma, Ziqi Zhang, Yuxin Chen +8
Understanding the content of events occurring in the video and their inherent temporal logic is crucial for video-text retrieval. However, web-crawled pre-training datasets often l…
MIBench: Evaluating Multimodal Large Language Models over Multiple Images
Haowei Liu, Xi Zhang, Haiyang Xu +8
Built on the power of LLMs, numerous multimodal large language models (MLLMs) have recently achieved remarkable performance on various vision-language tasks. However, most existing…
Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training
Haowei Liu, Yaya Shi, Haiyang Xu +8
In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment. However, in most existing methods, the recon…
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval
Haowei Liu, Yaya Shi, Haiyang Xu +8
In video-text retrieval, most existing methods adopt the dual-encoder architecture for fast retrieval, which employs two individual encoders to extract global latent representation…