activity
20182021
most citedParaCNN: Visual Paragraph Generation via Adversarial Twin Contextual CNNs

7 citations · 17 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV20211 cited

Fast and Accurate Scene Parsing via Bi-direction Alignment Networks

Yanran Wu, Xiangtai Li, Chen Shi +5

In this paper, we propose an effective method for fast and accurate scene parsing called Bidirectional Alignment Network (BiAlignNet). Previously, one representative work BiSeNet~\…

cs.CV2020

Off-Policy Self-Critical Training for Transformer in Visual Paragraph Generation

Shiyang Yan, Yang Hua, Neil M. Robertson

Recently, several approaches have been proposed to solve language generation problems. Transformer is currently state-of-the-art seq-to-seq model in language generation. Reinforcem…

cs.CV20207 cited

ParaCNN: Visual Paragraph Generation via Adversarial Twin Contextual CNNs

Shiyang Yan, Yang Hua, Neil Robertson

Image description generation plays an important role in many real-world applications, such as image retrieval, automatic navigation, and disabled people support. A well-developed t…

cs.CV2020

Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation

Yihan Du, Yan Yan, Si Chen +1

In recent years, deep learning based visual tracking methods have obtained great success owing to the powerful feature representation ability of Convolutional Neural Networks (CNNs…

cs.LG20195 cited

Instance Cross Entropy for Deep Metric Learning

Xinshao Wang, Elyor Kodirov, Yang Hua +1

Loss functions play a crucial role in deep metric learning thus a variety of them have been proposed. Some supervise the learning process by pairwise or tripletwise similarity cons…

cs.CV20193 cited

ID-aware Quality for Set-based Person Re-identification

Xinshao Wang, Elyor Kodirov, Yang Hua +1

Set-based person re-identification (SReID) is a matching problem that aims to verify whether two sets are of the same identity (ID). Existing SReID models typically generate a feat…