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Residual Attention: A Simple but Effective Method for Multi-Label Recognition


Aug 19, 2021
Ke Zhu, Jianxin Wu

* ICCV 2021, code: https://github.com/Kevinz-code/CSRA 

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Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach


Aug 11, 2021
Zeren Sun, Yazhou Yao, Xiu-Shen Wei, Yongshun Zhang, Fumin Shen, Jianxin Wu, Jian Zhang, Heng-Tao Shen

* accepted by ICCV 2021 

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Weakly Supervised Foreground Learning for Weakly Supervised Localization and Detection


Aug 03, 2021
Chen-Lin Zhang, Yin Li, Jianxin Wu

* Work in progress 

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A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications


Jun 17, 2021
Yun-Hao Cao, Jianxin Wu

* 17 pages, 9 figures, 10 tables 

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Salvage of Supervision in Weakly Supervised Detection


Jun 08, 2021
Lin Sui, Chen-Lin Zhang, Jianxin Wu


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Friends and Foes in Learning from Noisy Labels


Mar 28, 2021
Yifan Zhou, Yifan Ge, Jianxin Wu


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Distilling Virtual Examples for Long-tailed Recognition


Mar 28, 2021
Yin-Yin He, Jianxin Wu, Xiu-Shen Wei


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Rethinking Self-Supervised Learning: Small is Beautiful


Mar 25, 2021
Yun-Hao Cao, Jianxin Wu

* 12 pages 

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Mixup Without Hesitation


Jan 12, 2021
Hao Yu, Huanyu Wang, Jianxin Wu


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In Defense of Feature Mimicking for Knowledge Distillation


Nov 03, 2020
Guo-Hua Wang, Yifan Ge, Jianxin Wu


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Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation


Jul 03, 2020
Bin-Bin Gao, Xin-Xin Liu, Hong-Yu Zhou, Jianxin Wu, Xin Geng

* submitted to Pattern Recognition 

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Rethinking the Route Towards Weakly Supervised Object Localization


Mar 03, 2020
Chen-Lin Zhang, Yun-Hao Cao, Jianxin Wu

* Accepted by CVPR 2020; Corrected some typo in the paper; The code repository is https://github.com/tzzcl/PSOL 

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Neural Network Pruning with Residual-Connections and Limited-Data


Dec 02, 2019
Jian-Hao Luo, Jianxin Wu


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Neural Forest Learning


Nov 18, 2019
Yun-Hao Cao, Jianxin Wu

* 12 pages 

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Repetitive Reprediction Deep Decipher for Semi-Supervised Learning


Aug 09, 2019
Guo-Hua Wang, Jianxin Wu


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Deep Learning for Fine-Grained Image Analysis: A Survey


Jul 06, 2019
Xiu-Shen Wei, Jianxin Wu, Quan Cui

* Project page: http://www.weixiushen.com/project/Awesome_FGIA/Awesome_FGIA.html 

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Towards Real-Time Action Recognition on Mobile Devices Using Deep Models


Jun 17, 2019
Chen-Lin Zhang, Xin-Xin Liu, Jianxin Wu

* work in progress 

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Probabilistic End-to-end Noise Correction for Learning with Noisy Labels


Mar 19, 2019
Kun Yi, Jianxin Wu

* CVPR 2019 

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When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets


Dec 13, 2018
Hong-Yu Zhou, Avital Oliver, Jianxin Wu, Yefeng Zheng

* Technical report 

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Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification


Dec 11, 2018
Xiu-Shen Wei, Chen-Lin Zhang, Lingqiao Liu, Chunhua Shen, Jianxin Wu

* ACCV 2018 

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AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference


May 24, 2018
Jian-Hao Luo, Jianxin Wu

* Submitted to NIPS 2018 

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Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples


May 11, 2018
Xiu-Shen Wei, Peng Wang, Lingqiao Liu, Chunhua Shen, Jianxin Wu


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Vortex Pooling: Improving Context Representation in Semantic Segmentation


Apr 22, 2018
Chen-Wei Xie, Hong-Yu Zhou, Jianxin Wu


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Learning Effective Binary Visual Representations with Deep Networks


Mar 08, 2018
Jianxin Wu, Jian-Hao Luo

* 16 pages, 3 figures 

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Code Attention: Translating Code to Comments by Exploiting Domain Features


Nov 27, 2017
Wenhao Zheng, Hong-Yu Zhou, Ming Li, Jianxin Wu


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Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion


Nov 20, 2017
Weiyao Lin, Yang Mi, Jianxin Wu, Ke Lu, Hongkai Xiong

* accepted by AAAI 2018 

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