137 citations · 176 across the 12 of their papers we have counts for
12 papers
DAP-MAE: Domain-Adaptive Point Cloud Masked Autoencoder for Effective Cross-Domain Learning
Ziqi Gao, Qiufu Li, Linlin Shen
Compared to 2D data, the scale of point cloud data in different domains available for training, is quite limited. Researchers have been trying to combine these data of different do…
BCE vs. CE in Deep Feature Learning
Qiufu Li, Huibin Xiao, Linlin Shen
When training classification models, it expects that the learned features are compact within classes, and can well separate different classes. As the dominant loss function for tra…
Distilled Transformers with Locally Enhanced Global Representations for Face Forgery Detection
Yaning Zhang, Qiufu Li, Zitong Yu +1
Face forgery detection (FFD) is devoted to detecting the authenticity of face images. Although current CNN-based works achieve outstanding performance in FFD, they are susceptible…
WiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration
Xinxing Cheng, Xi Jia, Wenqi Lu +4
Deep image registration has demonstrated exceptional accuracy and fast inference. Recent advances have adopted either multiple cascades or pyramid architectures to estimate dense d…
EPL: Empirical Prototype Learning for Deep Face Recognition
Weijia Fan, Jiajun Wen, Xi Jia +3
Prototype learning is widely used in face recognition, which takes the row vectors of coefficient matrix in the last linear layer of the feature extraction model as the prototypes…
Rediscovering BCE Loss for Uniform Classification
Qiufu Li, Xi Jia, Jiancan Zhou +2
This paper introduces the concept of uniform classification, which employs a unified threshold to classify all samples rather than adaptive threshold classifying each individual sa…
UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognition
Qiufu Li, Xi Jia, Jiancan Zhou +2
Sample-to-class-based face recognition models can not fully explore the cross-sample relationship among large amounts of facial images, while sample-to-sample-based models require…
Activation Template Matching Loss for Explainable Face Recognition
Huawei Lin, Haozhe Liu, Qiufu Li +1
Can we construct an explainable face recognition network able to learn a facial part-based feature like eyes, nose, mouth and so forth, without any manual annotation or additionals…
WaveCNet: Wavelet Integrated CNNs to Suppress Aliasing Effect for Noise-Robust Image Classification
Qiufu Li, Linlin Shen, Sheng Guo +1
Though widely used in image classification, convolutional neural networks (CNNs) are prone to noise interruptions, i.e. the CNN output can be drastically changed by small image noi…
Neuron segmentation using 3D wavelet integrated encoder-decoder network
Qiufu Li, Linlin Shen
Motivation: 3D neuron segmentation is a key step for the neuron digital reconstruction, which is essential for exploring brain circuits and understanding brain functions. However,…
WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation
Qiufu Li, Linlin Shen
In deep networks, the lost data details significantly degrade the performances of image segmentation. In this paper, we propose to apply Discrete Wavelet Transform (DWT) to extract…
Wavelet Integrated CNNs for Noise-Robust Image Classification
Qiufu Li, Linlin Shen, Sheng Guo +1
Convolutional Neural Networks (CNNs) are generally prone to noise interruptions, i.e., small image noise can cause drastic changes in the output. To suppress the noise effect to th…