78 citations · 88 across the 5 of their papers we have counts for
5 papers
Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy Objects
Yue Fan, Ningjing Fan, Ivan Skorokhodov +5
We develop a method that recovers the surface, materials, and illumination of a scene from its posed multi-view images. In contrast to prior work, it does not require any additiona…
Revisiting Consistency Regularization for Semi-Supervised Learning
Yue Fan, Anna Kukleva, Bernt Schiele
Consistency regularization is one of the most widely-used techniques for semi-supervised learning (SSL). Generally, the aim is to train a model that is invariant to various data au…
CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning
Yue Fan, Dengxin Dai, Anna Kukleva +1
In this paper, we propose a novel co-learning framework (CoSSL) with decoupled representation learning and classifier learning for imbalanced SSL. To handle the data imbalance, we…
Analyzing the Dependency of ConvNets on Spatial Information
Yue Fan, Yongqin Xian, Max Maria Losch +1
Intuitively, image classification should profit from using spatial information. Recent work, however, suggests that this might be overrated in standard CNNs. In this paper, we are…
Parameter-Free Spatial Attention Network for Person Re-Identification
Haoran Wang, Yue Fan, Zexin Wang +2
Global average pooling (GAP) allows to localize discriminative information for recognition [40]. While GAP helps the convolution neural network to attend to the most discriminative…