4 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
Qiong Wu, Wei Yu, Yiyi Zhou +3
With ever increasing parameters and computation, vision-language pre-trained (VLP) models exhibit prohibitive expenditure in downstream task adaption. Recent endeavors mainly focus…
Approximated Prompt Tuning for Vision-Language Pre-trained Models
Qiong Wu, Shubin Huang, Yiyi Zhou +4
Prompt tuning is a parameter-efficient way to deploy large-scale pre-trained models to downstream tasks by adding task-specific tokens. In terms of vision-language pre-trained (VLP…
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting
Shubin Huang, Qiong Wu, Yiyi Zhou +4
Pre-trained language models (PLMs) have played an increasing role in multimedia research. In terms of vision-language (VL) tasks, they often serve as a language encoder and still r…
Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning
Qiong Wu, Jiahan Li, Pingyang Dai +4
Unsupervised domain adaptation person re-identification (Re-ID) aims to identify pedestrian images within an unlabeled target domain with an auxiliary labeled source-domain dataset…
CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification
Qiong Wu, Jiaer Xia, Pingyang Dai +3
Visible-infrared person re-identification (VI-ReID) is a task of matching the same individuals across the visible and infrared modalities. Its main challenge lies in the modality g…
Learning Task-oriented Disentangled Representations for Unsupervised Domain Adaptation
Pingyang Dai, Peixian Chen, Qiong Wu +4
Unsupervised domain adaptation (UDA) aims to address the domain-shift problem between a labeled source domain and an unlabeled target domain. Many efforts have been made to address…