80 citations · 93 across the 7 of their papers we have counts for
7 papers
1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification Track
Yilu Guo, Xingyue Shi, Weijie Chen +4
OOD-CV challenge is an out-of-distribution generalization task. In this challenge, our core solution can be summarized as that Noisy Label Learning Is A Strong Test-Time Domain Ada…
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach
Yilu Guo, Shicai Yang, Weijie Chen +3
Convolutional neural networks (CNNs) have achieved significant success in image classification by utilizing large-scale datasets. However, it is still of great challenge to learn f…
Box Re-Ranking: Unsupervised False Positive Suppression for Domain Adaptive Pedestrian Detection
Weijie Chen, Yilu Guo, Shicai Yang +7
False positive is one of the most serious problems brought by agnostic domain shift in domain adaptive pedestrian detection. However, it is impossible to label each box in countles…
Unsupervised Image Classification for Deep Representation Learning
Weijie Chen, Shiliang Pu, Di Xie +3
Deep clustering against self-supervised learning is a very important and promising direction for unsupervised visual representation learning since it requires little domain knowled…
Deep Differentiable Random Forests for Age Estimation
Wei Shen, Yilu Guo, Yan Wang +3
Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feat…
Deep Regression Forests for Age Estimation
Wei Shen, Yilu Guo, Yan Wang +3
Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is heterogeneous,…
Label Distribution Learning Forests
Wei Shen, Kai Zhao, Yilu Guo +1
Label distribution learning (LDL) is a general learning framework, which assigns to an instance a distribution over a set of labels rather than a single label or multiple labels. C…