1 code implementation • 19 Jan 2023 • Huafeng Liu, Pai Peng, Tao Chen, Qiong Wang, Yazhou Yao, Xian-Sheng Hua
Few-shot semantic segmentation is the task of learning to locate each pixel of the novel class in the query image with only a few annotated support images.
Ranked #2 on Few-Shot Semantic Segmentation on COCO-20i (10-shot)
2 code implementations • ICCV 2021 • Jiaqi Wang, Huafeng Liu, Xinyue Wang, Liping Jing
This plug-in embedding space is spanned by transparent basis concepts which are constructed on the Grassmann manifold.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2023 • Xinyue Wang, Liping Jing, Yilin Lyu, Mingzhe Guo, Jiaqi Wang, Huafeng Liu, Jian Yu, and Tieyong Zeng
In this paper, a deep generative classifier is proposed to mitigate this issue via both model perturbation and data perturbation.
1 code implementation • 29 Feb 2024 • Gensheng Pei, Tao Chen, Xiruo Jiang, Huafeng Liu, Zeren Sun, Yazhou Yao
In this paper, we propose a new approach termed as \textbf{VideoMAC}, which combines video masked autoencoders with resource-friendly ConvNets.
1 code implementation • 23 Mar 2023 • Mingyang Song, Haiyun Jiang, Shuming Shi, Songfang Yao, Shilong Lu, Yi Feng, Huafeng Liu, Liping Jing
Based on our findings, we conclude that ChatGPT has great potential for keyphrase generation.
1 code implementation • 23 Jan 2021 • Huafeng Liu, Chuanyi Zhang, Yazhou Yao, Xiushen Wei, Fumin Shen, Jian Zhang, Zhenmin Tang
Labeling objects at a subordinate level typically requires expert knowledge, which is not always available when using random annotators.
no code implementations • 26 May 2019 • Huafeng Liu, Yazhou Yao, Zeren Sun, Xiangrui Li, Ke Jia, Zhenmin Tang
Robust road segmentation is a key challenge in self-driving research.
no code implementations • 26 May 2019 • Huafeng Liu, Xiaofeng Han, Xiangrui Li, Yazhou Yao, Pu Huang, Zhenming Tang
We project the LiDAR point clouds onto the image plane to generate LiDAR images and feed them into one of the branches of the network.
no code implementations • 24 Jul 2019 • Ming Li, Weiwei Zhang, Guang Yang, Chengjia Wang, Heye Zhang, Huafeng Liu, Wei Zheng, Shuo Li
Our method is built as an end-to-end framework for segmentation and classification.
no code implementations • 16 Dec 2019 • Nuobei Xie, Kuang Gong, Ning Guo, Zhixin Qin, Zhifang Wu, Huafeng Liu, Quanzheng Li
Positron emission tomography (PET) is widely used for clinical diagnosis.
no code implementations • 13 Sep 2020 • Nuobei Xie, Kuang Gong, Ning Guo, Zhixing Qin, Jianan Cui, Zhifang Wu, Huafeng Liu, Quanzheng Li
Patlak model is widely used in 18F-FDG dynamic positron emission tomography (PET) imaging, where the estimated parametric images reveal important biochemical and physiology information.
no code implementations • 14 Sep 2020 • Jianan Cui, Kuang Gong, Paul Han, Huafeng Liu, Quanzheng Li
After the network was trained, the super-resolution (SR) image was generated by supplying the upsampled LR ASL image and corresponding T1-weighted image to the generator of the last layer.
no code implementations • CVPR 2021 • Huafeng Liu, Jiaqi Wang, Liping Jing
In this paper, we propose Cluster-wise Hierarchical Generative Model for deep amortized clustering (CHiGac).
no code implementations • 9 May 2022 • Rui Hu, Huafeng Liu
Positron emission tomography(PET) image reconstruction is an ill-posed inverse problem and suffers from high level of noise due to limited counts received.
no code implementations • 23 May 2022 • Yihang Gao, Huafeng Liu, Michael K. Ng, Mingjie Zhou
Wide applications of differentiable two-player sequential games (e. g., image generation by GANs) have raised much interest and attention of researchers to study efficient and fast algorithms.
no code implementations • 21 Feb 2023 • Chenxu Li, Rui Hu, Jianan Cui, Huafeng Liu
Additionally, we compare the spatial and temporal consumption of list-mode data and sinogram data in model-based deep learning methods, demonstrating the superiority of list-mode data in model-based TOF-PET reconstruction.
no code implementations • 8 Mar 2023 • Rui Hu, Jianan Cui, Chengjin Yu, YunMei Chen, Huafeng Liu
Dynamic positron emission tomography (dPET) image reconstruction is extremely challenging due to the limited counts received in individual frame.
no code implementations • 8 Mar 2023 • Rui Hu, YunMei Chen, Kyungsang Kim, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Quanzheng Li, Huafeng Liu
Deep learning based PET image reconstruction methods have achieved promising results recently.
no code implementations • AAAI 2022 • Huafeng Liu, Tong Zhou, Jiaqi Wang, Liping Jing
In this paper, we propose Deep amortized Relational Model (DaRM) with group-wise hierarchical generative process for community discovery and link prediction on relational data (e. g., graph, network).
no code implementations • MM '22: Proceedings of the 30th ACM International Conference on Multimedia 2022 • Huafeng Liu, Liping Jing, Dahai Yu, Mingjie Zhou, Michael Ng
In this paper, we propose an intention neural process model (INP) for user cold-start recommendation (i. e., user with very few historical interactions), a novel extension of the neural stochastic process family using a general meta learning strategy with intrinsic and extrinsic intention learning for robust user preference learning.
no code implementations • 9 Nov 2023 • Huafeng Liu, Benjamin Dowdell, Todd Engelder, Zarah Pulmano, Nicolas Osa, Arko Barman
Analysis of Magnetic Resonance Imaging (MRI) scans is one of the most effective methods for the diagnosis and treatment of brain cancers such as glioblastoma.
no code implementations • 17 Feb 2024 • Huafeng Liu, Mengmeng Sheng, Zeren Sun, Yazhou Yao, Xian-Sheng Hua, Heng-Tao Shen
Specifically, we propose Class-Balance-based sample Selection (CBS) to prevent the tail class samples from being neglected during training.
no code implementations • 12 Mar 2024 • Yubo Ye, Huafeng Liu, Linwei Wang
We then embed this hybrid model at the latent space of an encoding-decoding framework to enable both supervised and unsupervised identification of the hybrid kinetics and thereby dynamic PET reconstruction.
no code implementations • 13 Mar 2024 • Yubo Ye, Sumeet Vadhavkar, Xiajun Jiang, Ryan Missel, Huafeng Liu, Linwei Wang
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series.