activity
20172021
most citedDistilling Knowledge from Graph Convolutional Networks

21 citations · 35 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021★ 1 cited

Unsupervised Person Re-identification via Simultaneous Clustering and Consistency Learning

Junhui Yin, Jiayan Qiu, Siqing Zhang +3

Unsupervised person re-identification (re-ID) has become an important topic due to its potential to resolve the scalability problem of supervised re-ID models. However, existing me…

cs.CV2020

Learning Propagation Rules for Attribution Map Generation

Yiding Yang, Jiayan Qiu, Mingli Song +2

Prior gradient-based attribution-map methods rely on handcrafted propagation rules for the non-linear/activation layers during the backward pass, so as to produce gradients of the…

cs.CV2020★ 1 cited

SSKD: Self-Supervised Knowledge Distillation for Cross Domain Adaptive Person Re-Identification

Junhui Yin, Jiayan Qiu, Siqing Zhang +2

Domain adaptive person re-identification (re-ID) is a challenging task due to the large discrepancy between the source domain and the target domain. To reduce the domain discrepanc…

cs.CV2020★ 21 cited

Distilling Knowledge from Graph Convolutional Networks

Yiding Yang, Jiayan Qiu, Mingli Song +2

Existing knowledge distillation methods focus on convolutional neural networks (CNNs), where the input samples like images lie in a grid domain, and have largely overlooked graph c…

stat.ML2017★ 12 cited

Towards Evolutional Compression

Yunhe Wang, Chang Xu, Jiayan Qiu +2

Compressing convolutional neural networks (CNNs) is essential for transferring the success of CNNs to a wide variety of applications to mobile devices. In contrast to directly reco…