6 citations · 22 across the 6 of their papers we have counts for
6 papers
Unsupervised Finetuning
Suichan Li, Dongdong Chen, Yinpeng Chen +5
This paper studies "unsupervised finetuning", the symmetrical problem of the well-known "supervised finetuning". Given a pretrained model and small-scale unlabeled target data, uns…
Improve Unsupervised Pretraining for Few-label Transfer
Suichan Li, Dongdong Chen, Yinpeng Chen +5
Unsupervised pretraining has achieved great success and many recent works have shown unsupervised pretraining can achieve comparable or even slightly better transfer performance th…
Are Fewer Labels Possible for Few-shot Learning?
Suichan Li, Dongdong Chen, Yinpeng Chen +4
Few-shot learning is challenging due to its very limited data and labels. Recent studies in big transfer (BiT) show that few-shot learning can greatly benefit from pretraining on l…
Density-Aware Graph for Deep Semi-Supervised Visual Recognition
Suichan Li, Bin Liu, Dongdong Chen +3
Semi-supervised learning (SSL) has been extensively studied to improve the generalization ability of deep neural networks for visual recognition. To involve the unlabelled data, mo…
Memory-Based Neighbourhood Embedding for Visual Recognition
Suichan Li, Dapeng Chen, Bin Liu +2
Learning discriminative image feature embeddings is of great importance to visual recognition. To achieve better feature embeddings, most current methods focus on designing differe…
3D-DETNet: a Single Stage Video-Based Vehicle Detector
Suichan Li
Video-based vehicle detection has received considerable attention over the last ten years and there are many deep learning based detection methods which can be applied to it. Howev…