activity
20172022
most citedAdversarial Generation of Training Examples: Applications to Moving Vehicle License Plate Recognition

37 citations · 48 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO20227 cited

Weakly Supervised Disentangled Representation for Goal-conditioned Reinforcement Learning

Zhifeng Qian, Mingyu You, Hongjun Zhou +1

Goal-conditioned reinforcement learning is a crucial yet challenging algorithm which enables agents to achieve multiple user-specified goals when learning a set of skills in a dyna…

cs.CV20204 cited

Diverse Knowledge Distillation for End-to-End Person Search

Xinyu Zhang, Xinlong Wang, Jia-Wang Bian +2

Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches.…

cs.CV2020

Mask Encoding for Single Shot Instance Segmentation

Rufeng Zhang, Zhi Tian, Chunhua Shen +2

To date, instance segmentation is dominated by twostage methods, as pioneered by Mask R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP, mainly d…

cs.CV2019

Part-Guided Attention Learning for Vehicle Instance Retrieval

Xinyu Zhang, Rufeng Zhang, Jiewei Cao +3

Vehicle instance retrieval often requires one to recognize the fine-grained visual differences between vehicles. Besides the holistic appearance of vehicles which is easily affecte…

cs.CV2019

Self-training with progressive augmentation for unsupervised cross-domain person re-identification

Xinyu Zhang, Jiewei Cao, Chunhua Shen +1

Person re-identification (Re-ID) has achieved great improvement with deep learning and a large amount of labelled training data. However, it remains a challenging task for adapting…

cs.CV201737 cited

Adversarial Generation of Training Examples: Applications to Moving Vehicle License Plate Recognition

Xinlong Wang, Zhipeng Man, Mingyu You +1

Generative Adversarial Networks (GAN) have attracted much research attention recently, leading to impressive results for natural image generation. However, to date little success w…