no code implementations • ECCV 2020 • Jiaxin Chen, Jie Qin, Yuming Shen, Li Liu, Fan Zhu, Ling Shao
This paper proposes a novel method for 3D shape representation learning, namely Hyperbolic Embedded Attentive Representation (HEAR).
no code implementations • 18 Jul 2023 • Menghan Wang, Jinming Yang, Yuchen Guo, Yuming Shen, Mengying Zhu, Yanlin Wang
Inspired by recent advances on differentiable sorting, in this paper, we propose a novel multi-task framework that leverages orders of user behaviors to predict user post-click conversion in an end-to-end approach.
no code implementations • 7 Feb 2023 • Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Yawen Cui, Jiehua Zhang, Philip Torr, Guoying Zhao
As key modules in PhysFormer, the temporal difference transformers first enhance the quasi-periodic rPPG features with temporal difference guided global attention, and then refine the local spatio-temporal representation against interference.
no code implementations • 23 Nov 2022 • Dubing Chen, Haofeng Zhang, Yuming Shen, Yang Long, Ling Shao
In this work, we propose a novel Evolutionary Generalized Zero-Shot Learning setting, which (i) avoids the domain shift problem in inductive GZSL, and (ii) is more in line with the needs of real-world deployments than transductive GZSL.
no code implementations • 19 Nov 2022 • Chenyi Jiang, Dubing Chen, Shidong Wang, Yuming Shen, Haofeng Zhang, Ling Shao
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen compositions from seen states and objects.
no code implementations • 13 Jul 2022 • Ziyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti, Vasilis Stavrinides, Richard Fan, Caroline Moore, Mirabela Rusu, Geoffrey Sonn, Philip Torr, Dean Barratt, Yipeng Hu
Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients.
1 code implementation • 25 Apr 2022 • Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr
As a consequence of our derivation, the aforementioned two properties are incorporated into the classifier training as seen-unseen priors via logit adjustment.
Ranked #1 on Generalized Zero-Shot Learning on AwA2 (Accuracy Unseen metric)
1 code implementation • 24 Apr 2022 • Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr
Recent research on Generalized Zero-Shot Learning (GZSL) has focused primarily on generation-based methods.
no code implementations • 18 Apr 2022 • Menghan Wang, Yuchen Guo, Zhenqi Zhao, Guangzheng Hu, Yuming Shen, Mingming Gong, Philip Torr
To alleviate the influence of the annotation bias, we perform a momentum update to ensure a consistent item representation.
no code implementations • 31 Jan 2022 • Jiaguo Yu, Yuming Shen, Menghan Wang, Haofeng Zhang, Philip H. S. Torr
In this paper, we tackle this problem by introducing Naturally-Sorted Hashing (NSH).
1 code implementation • 23 Dec 2021 • Xiaojie Zhao, Yuming Shen, Shidong Wang, Haofeng Zhang
Most generative ZSL methods use category semantic attributes plus a Gaussian noise to generate visual features.
1 code implementation • CVPR 2022 • Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao
Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applications (e. g., remote healthcare and affective computing).
no code implementations • ACL 2021 • Xinying Qiu, Yuan Chen, Hanwu Chen, Jian-Yun Nie, Yuming Shen, Dawei Lu
Deep learning models for automatic readability assessment generally discard linguistic features traditionally used in machine learning models for the task.
no code implementations • NeurIPS 2021 • Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H. S. Torr, Ling Shao
On one hand, with the corresponding assignment variables being the weight, a weighted aggregation along the data points implements the set representation of a cluster.
1 code implementation • ECCV 2020 • Yuming Shen, Jie Qin, Lei Huang
Deep generative models have been successfully applied to Zero-Shot Learning (ZSL) recently.
2 code implementations • CVPR 2020 • Yuming Shen, Jie Qin, Jiaxin Chen, Mengyang Yu, Li Liu, Fan Zhu, Fumin Shen, Ling Shao
One bottleneck (i. e., binary codes) conveys the high-level intrinsic data structure captured by the code-driven graph to the other (i. e., continuous variables for low-level detail information), which in turn propagates the updated network feedback for the encoder to learn more discriminative binary codes.
1 code implementation • 26 Aug 2019 • Yuming Shen, Jie Qin, Jiaxin Chen, Li Liu, Fan Zhu
Recent binary representation learning models usually require sophisticated binary optimization, similarity measure or even generative models as auxiliaries.
1 code implementation • CVPR 2018 • Yuming Shen, Li Liu, Fumin Shen, Ling Shao
As an important part of ZSIH, we formulate a generative hashing scheme in reconstructing semantic knowledge representations for zero-shot retrieval.
no code implementations • ICCV 2017 • Yuming Shen, Li Liu, Ling Shao, Jingkuan Song
Cross-modal hashing is usually regarded as an effective technique for large-scale textual-visual cross retrieval, where data from different modalities are mapped into a shared Hamming space for matching.
1 code implementation • CVPR 2017 • Li Liu, Fumin Shen, Yuming Shen, Xianglong Liu, Ling Shao
Free-hand sketch-based image retrieval (SBIR) is a specific cross-view retrieval task, in which queries are abstract and ambiguous sketches while the retrieval database is formed with natural images.