no code implementations • 18 Oct 2021 • Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu
This problem is more challenging than the supervised counterpart, as the low data density in the small-scale target data is not friendly for unsupervised learning, leading to the damage of the pretrained representation and poor representation in the target domain.
no code implementations • ICCV 2021 • Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu
Unsupervised pretraining has achieved great success and many recent works have shown unsupervised pretraining can achieve comparable or even slightly better transfer performance than supervised pretraining on downstream target datasets.
no code implementations • 10 Dec 2020 • Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Nenghai Yu
We conduct experiments on 10 different few-shot target datasets, and our average few-shot performance outperforms both vanilla inductive unsupervised transfer and supervised transfer by a large margin.
no code implementations • CVPR 2020 • Suichan Li, Bin Liu, Dong-Dong Chen, Qi Chu, Lu Yuan, Nenghai Yu
Motivated by these limitations, this paper proposes to solve the SSL problem by building a novel density-aware graph, based on which the neighborhood information can be easily leveraged and the feature learning and label propagation can also be trained in an end-to-end way.
no code implementations • ICCV 2019 • Suichan Li, Dapeng Chen, Bin Liu, Nenghai Yu, Rui Zhao
Learning discriminative image feature embeddings is of great importance to visual recognition.
no code implementations • 5 Jan 2018 • 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.
Ranked #9 on Object Detection on UA-DETRAC