6 citations · 24 across the 10 of their papers we have counts for
10 papers
Attribute-Aware Implicit Modality Alignment for Text Attribute Person Search
Xin Wang, Fangfang Liu, Zheng Li +1
Text attribute person search aims to find specific pedestrians through given textual attributes, which is very meaningful in the scene of searching for designated pedestrians throu…
Data Augmentation for Text-based Person Retrieval Using Large Language Models
Zheng Li, Lijia Si, Caili Guo +2
Text-based Person Retrieval (TPR) aims to retrieve person images that match the description given a text query. The performance improvement of the TPR model relies on high-quality…
Boundary-Aware Proposal Generation Method for Temporal Action Localization
Hao Zhang, Chunyan Feng, Jiahui Yang +2
The goal of Temporal Action Localization (TAL) is to find the categories and temporal boundaries of actions in an untrimmed video. Most TAL methods rely heavily on action recogniti…
Integrating Listwise Ranking into Pairwise-based Image-Text Retrieval
Zheng Li, Caili Guo, Xin Wang +2
Image-Text Retrieval (ITR) is essentially a ranking problem. Given a query caption, the goal is to rank candidate images by relevance, from large to small. The current ITR datasets…
Selectively Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching
Zheng Li, Caili Guo, Xin Wang +2
Recently, a series of Image-Text Matching (ITM) methods achieve impressive performance. However, we observe that most existing ITM models suffer from gradients vanishing at the beg…
Image-Text Retrieval with Binary and Continuous Label Supervision
Zheng Li, Caili Guo, Zerun Feng +3
Most image-text retrieval work adopts binary labels indicating whether a pair of image and text matches or not. Such a binary indicator covers only a limited subset of image-text s…
Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval
Zheng Li, Caili Guo, Xin Wang +3
There are two popular loss functions used for vision-language retrieval, i.e., triplet loss and contrastive learning loss, both of them essentially minimize the difference between…
Exploiting Visual Semantic Reasoning for Video-Text Retrieval
Zerun Feng, Zhimin Zeng, Caili Guo +1
Video retrieval is a challenging research topic bridging the vision and language areas and has attracted broad attention in recent years. Previous works have been devoted to repres…
Multi-Agent Deep Reinforcement Learning based Spectrum Allocation for D2D Underlay Communications
Zheng Li, Caili Guo
Device-to-device (D2D) communication underlay cellular networks is a promising technique to improve spectrum efficiency. In this situation, D2D transmission may cause severe interf…
A Multi-Agent Deep Reinforcement Learning based Spectrum Allocation Framework for D2D Communications
Zheng Li, Caili Guo, Yidi Xuan
Device-to-device (D2D) communication has been recognized as a promising technique to improve spectrum efficiency. However, D2D transmission as an underlay causes severe interferenc…