15 citations · 29 across the 9 of their papers we have counts for
9 papers
Exploring Shape Embedding for Cloth-Changing Person Re-Identification via 2D-3D Correspondences
Yubin Wang, Huimin Yu, Yuming Yan +3
Cloth-Changing Person Re-Identification (CC-ReID) is a common and realistic problem since fashion constantly changes over time and people's aesthetic preferences are not set in sto…
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning
Guodong Qi, Huimin Yu
Unsupervised meta-learning aims to learn the meta knowledge from unlabeled data and rapidly adapt to novel tasks. However, existing approaches may be misled by the context-bias (e.…
Searching Similarity Measure for Binarized Neural Networks
Yanfei Li, Ang Li, Huimin Yu
Being a promising model to be deployed in resource-limited devices, Binarized Neural Networks (BNNs) have drawn extensive attention from both academic and industry. However, compar…
GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Feature
Biyang Liu, Huimin Yu, Guodong Qi
Although supervised deep stereo matching networks have made impressive achievements, the poor generalization ability caused by the domain gap prevents them from being applied to re…
Gated Domain-Invariant Feature Disentanglement for Domain Generalizable Object Detection
Haozhuo Zhang, Huimin Yu, Yuming Yan +1
For Domain Generalizable Object Detection (DGOD), Disentangled Representation Learning (DRL) helps a lot by explicitly disentangling Domain-Invariant Representations (DIR) from Dom…
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Biyang Liu, Huimin Yu, Yangqi Long
Although convolution neural network based stereo matching architectures have made impressive achievements, there are still some limitations: 1) Convolutional Feature (CF) tends to…
Transductive Few-Shot Classification on the Oblique Manifold
Guodong Qi, Huimin Yu, Zhaohui Lu +1
Few-shot learning (FSL) attempts to learn with limited data. In this work, we perform the feature extraction in the Euclidean space and the geodesic distance metric on the Oblique…
Fractal Pyramid Networks
Zhiqiang Deng, Huimin Yu, Yangqi Long
We propose a new network architecture, the Fractal Pyramid Networks (PFNs) for pixel-wise prediction tasks as an alternative to the widely used encoder-decoder structure. In the en…
BCNN: Binary Complex Neural Network
Yanfei Li, Tong Geng, Ang Li +1
Binarized neural networks, or BNNs, show great promise in edge-side applications with resource limited hardware, but raise the concerns of reduced accuracy. Motivated by the comple…