Winner Presentation - Image Track : Winner id: #1 (09:30 - 09:39)

Team Name: Smart Image

Team Member: Lingxi Xie, Xiaopeng Zhang, Bingcheng Liu, Zhao Yang, Zewei Du, Hang Chen, Longhui Wei, Yaxiong Chi

Team Affiliation: Huawei Cloud & Huawei 2012 Labs

Method Description (short) : Our work is implemented on Huawei ModelArts platform [1], which slightly improves accuracy while being much faster in training. As for the algorithms, the main idea is to leverage area under the margin and knowledge distillation for handling noise labels, as well as an algorithm for learning an ensemble model.

Method Description : Our work is implemented on Huawei ModelArts platform [1], which slightly improves accuracy while being much faster in training. As for the algorithms, the main idea is to leverage area under the margin and knowledge distillation for handling noise labels, as well as an algorithm for learning an ensemble model.
The details are as follows:
a. We use different types of state-of-the-art network architectures, including ResNeXt、ResNeSt、seNet and SE-ResNeXt;
b. We use the Area Under the Margin (AUM) algorithm [2] and knowledge distillation [3] for handling noise label;
c. Curriculum learning strategy is used to refine the network many times;
d. Training models with large resolution can improve model performance;
e. During testing, we apply multi-scale and multi-crop to each test image;
f. We also ensemble different models using different strategies.
[1] What Is ModelArts? https://support.huaweicloud.com/en-us/productdesc-modelarts/modelarts_01_0001.html
[2] Identifying Mislabeled Data using the Area Under the Margin Ranking. arXiv preprint arXiv:2001.10528 (2020).
[3] Learning from Noisy Labels with Distillation. ICCV. 2017.

Entry Description :
Entry 1: model ensemble with weighted average
Entry 2: model ensemble with different weights
Entry 3: model distillation + model ensemble with weighted average
Entry 4: model distillation + model ensemble with different weights
Entry 5: model ensemble (heuristic algorithm)