22 citations · 22 across the 6 of their papers we have counts for
6 papers
T2VParser: Adaptive Decomposition Tokens for Partial Alignment in Text to Video Retrieval
Yili Li, Gang Xiong, Gaopeng Gou +4
Text-to-video retrieval essentially aims to train models to align visual content with textual descriptions accurately. Due to the impressive general multimodal knowledge demonstrat…
MADS: Multi-Attribute Document Supervision for Zero-Shot Image Classification
Xiangyan Qu, Jing Yu, Jiamin Zhuang +3
Zero-shot learning (ZSL) aims to train a model on seen classes and recognize unseen classes by knowledge transfer through shared auxiliary information. Recent studies reveal that d…
ProAPO: Progressively Automatic Prompt Optimization for Visual Classification
Xiangyan Qu, Gaopeng Gou, Jiamin Zhuang +5
Vision-language models (VLMs) have made significant progress in image classification by training with large-scale paired image-text data. Their performances largely depend on the p…
Visual-Semantic Decomposition and Partial Alignment for Document-based Zero-Shot Learning
Xiangyan Qu, Jing Yu, Keke Gai +5
Recent work shows that documents from encyclopedias serve as helpful auxiliary information for zero-shot learning. Existing methods align the entire semantics of a document with co…
Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service
Yuanmin Tang, Jing Yu, Keke Gai +4
Recent advances in vision-language pre-trained models (VLPs) have significantly increased visual understanding and cross-modal analysis capabilities. Companies have emerged to prov…
Towards Fast and Accurate Image-Text Retrieval with Self-Supervised Fine-Grained Alignment
Jiamin Zhuang, Jing Yu, Yang Ding +2
Image-text retrieval requires the system to bridge the heterogenous gap between vision and language for accurate retrieval while keeping the network lightweight-enough for efficien…