24 citations · 25 across the 6 of their papers we have counts for
6 papers
ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval
Zixu Li, Yupeng Hu, Zhiwei Chen +3
The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on expensive and error-prone tripl…
HINT: Composed Image Retrieval with Dual-path Compositional Contextualized Network
Mingyu Zhang, Zixu Li, Zhiwei Chen +5
Composed Image Retrieval (CIR) is a challenging image retrieval paradigm. It aims to retrieve target images from large-scale image databases that are consistent with the modificati…
STAR-GNN: Spatial-Temporal Video Representation for Content-based Retrieval
Guoping Zhao, Bingqing Zhang, Mingyu Zhang +3
We propose a video feature representation learning framework called STAR-GNN, which applies a pluggable graph neural network component on a multi-scale lattice feature graph. The e…
InvisibiliTee: Angle-agnostic Cloaking from Person-Tracking Systems with a Tee
Yaxian Li, Bingqing Zhang, Guoping Zhao +4
After a survey for person-tracking system-induced privacy concerns, we propose a black-box adversarial attack method on state-of-the-art human detection models called InvisibiliTee…
Modality-Balanced Embedding for Video Retrieval
Xun Wang, Bingqing Ke, Xuanping Li +6
Video search has become the main routine for users to discover videos relevant to a text query on large short-video sharing platforms. During training a query-video bi-encoder mode…
Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN
Guoping Zhao, Mingyu Zhang, Jiajun Liu +1
Studies show that Deep Neural Network (DNN)-based image classification models are vulnerable to maliciously constructed adversarial examples. However, little effort has been made t…