output
20032024
most citedImproving the security of multiparty quantum secret sharing against Trojan horse attack

580 citations

Showing cs.CVShow all

18 papers · 1 filter

cs.CV20249 cited

Text-Region Matching for Multi-Label Image Recognition with Missing Labels

Leilei Ma, Hongxing Xie, Lei Wang +3

Recently, large-scale visual language pre-trained (VLP) models have demonstrated impressive performance across various downstream tasks. Motivated by these advancements, pioneering…

cs.CV2023145 cited

HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection

Bin Tang, Zhengyi Liu, Yacheng Tan +1

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation and share global receptive fields. It is friendly towards salient object detection (SOD) in w…

cs.CV2022381 cited

SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection

Zhengyi Liu, Yacheng Tan, Qian He +1

Convolutional neural networks (CNNs) are good at extracting contexture features within certain receptive fields, while transformers can model the global long-range dependency featu…

cs.CV2021

Tracking by Joint Local and Global Search: A Target-aware Attention based Approach

Xiao Wang, Jin Tang, Bin Luo +3

Tracking-by-detection is a very popular framework for single object tracking which attempts to search the target object within a local search window for each frame. Although such l…

cs.CV20208 cited

Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Lingbo Liu, Jiaqi Chen, Hefeng Wu +3

Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited…

cs.CV20204 cited

Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification

Aihua Zheng, Xia Sun, Chenglong Li +1

Vehicle re-identification (Re-ID) is an active task due to its importance in large-scale intelligent monitoring in smart cities. Despite the rapid progress in recent years, most ex…