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2020 – today
- 2023
[j6]Jinghong Peng, Jun Zhou, Guangchuan Liang, Can Qin, Cao Peng, YuLin Chen, Chengqiang Hu:
Global layout optimization of star-tree gas gathering pipeline network via an improved genetic optimization algorithm. J. Intell. Fuzzy Syst. 44(2): 2655-2672 (2023)- [j5]Huan Wang
, Yulun Zhang, Can Qin, Luc Van Gool, Yun Fu:
Global Aligned Structured Sparsity Learning for Efficient Image Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 10974-10989 (2023) - [j4]Joseph P. Robinson, Can Qin, Yann Henon, Samson Timoner, Yun Fu:
Balancing Biases and Preserving Privacy on Balanced Faces in the Wild. IEEE Trans. Image Process. 32: 4365-4377 (2023) - [c26]Vibashan VS, Ning Yu, Chen Xing, Can Qin, Mingfei Gao, Juan Carlos Niebles, Vishal M. Patel, Ran Xu:
Mask-Free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations. CVPR 2023: 23539-23549 - [c25]Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu:
Image as Set of Points. ICLR 2023 - [i23]Huan Wang, Can Qin, Yue Bai, Yun Fu:
Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning. CoRR abs/2301.05219 (2023) - [i22]Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, Yun Fu:
Making Reconstruction-based Method Great Again for Video Anomaly Detection. CoRR abs/2301.12048 (2023) - [i21]Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu:
Image as Set of Points. CoRR abs/2303.01494 (2023) - [i20]Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, Caiming Xiong, Ran Xu:
HIVE: Harnessing Human Feedback for Instructional Visual Editing. CoRR abs/2303.09618 (2023) - [i19]Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, Ran Xu:
GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation. CoRR abs/2303.10056 (2023) - [i18]Vibashan VS, Ning Yu, Chen Xing, Can Qin, Mingfei Gao, Juan Carlos Niebles, Vishal M. Patel, Ran Xu:
Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations. CoRR abs/2303.16891 (2023) - [i17]Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang, Yingbo Zhou, Huan Wang, Juan Carlos Niebles, Caiming Xiong, Silvio Savarese, Stefano Ermon, Yun Fu, Ran Xu:
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild. CoRR abs/2305.11147 (2023) - [i16]Haichao Zhang, Can Qin, Yu Yin, Yun Fu:
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection. CoRR abs/2308.06701 (2023) - 2022
- [j3]Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu:
Semi-Supervised Domain Adaptive Structure Learning. IEEE Trans. Image Process. 31: 7179-7190 (2022) - [c24]Can Qin, Yizhou Wang, Yun Fu:
Robust Semi-supervised Domain Adaptation against Noisy Labels. CIKM 2022: 4409-4413 - [c23]Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu:
Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection. CIKM 2022: 4555-4559 - [c22]Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, Yun Fu:
Making Reconstruction-based Method Great Again for Video Anomaly Detection. ICDM 2022: 1215-1220 - [c21]Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu:
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework. ICLR 2022 - [c20]Yulun Zhang, Huan Wang, Can Qin, Yun Fu:
Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning. ICLR 2022 - [c19]Yi Xu, Lichen Wang, Yizhou Wang, Can Qin, Yulun Zhang, Yun Fu:
MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning. IJCAI 2022: 3636-3642 - [c18]Huan Wang, Can Qin, Yue Bai, Yulun Zhang, Yun Fu:
Recent Advances on Neural Network Pruning at Initialization. IJCAI 2022: 5638-5645 - [c17]Can Qin, Sungchul Kim, Handong Zhao, Tong Yu, Ryan A. Rossi, Yun Fu:
External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters. KDD 2022: 1401-1409 - [i15]Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu:
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework. CoRR abs/2202.07123 (2022) - [i14]Xu Ma, Huan Wang, Can Qin, Kunpeng Li, Xingchen Zhao, Jie Fu, Yun Fu:
A Close Look at Spatial Modeling: From Attention to Convolution. CoRR abs/2212.12552 (2022) - 2021
- [j2]Lichen Wang, Yunyu Liu, Hang Di, Can Qin, Gan Sun, Yun Fu:
Semi-Supervised Dual Relation Learning for Multi-Label Classification. IEEE Trans. Image Process. 30: 9125-9135 (2021) - [c16]Joseph P. Robinson, Can Qin, Ming Shao, Matthew A. Turk, Rama Chellappa, Yun Fu:
The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces. FG 2021: 1-7 - [c15]Yulun Zhang, Donglai Wei, Can Qin, Huan Wang, Hanspeter Pfister, Yun Fu:
Context Reasoning Attention Network for Image Super-Resolution. ICCV 2021: 4258-4267 - [c14]Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu:
Aspect-based Sentiment Classification via Reinforcement Learning. ICDM 2021: 1391-1396 - [c13]Huan Wang, Can Qin, Yulun Zhang, Yun Fu:
Neural Pruning via Growing Regularization. ICLR 2021 - [c12]Yu Yin, Joseph P. Robinson, Songyao Jiang, Yue Bai, Can Qin, Yun Fu:
SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis. ACM Multimedia 2021: 1609-1617 - [c11]Yulun Zhang, Huan Wang, Can Qin, Yun Fu:
Aligned Structured Sparsity Learning for Efficient Image Super-Resolution. NeurIPS 2021: 2695-2706 - [c10]Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu:
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation. NeurIPS 2021: 14110-14121 - [c9]Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu:
Contradictory Structure Learning for Semi-supervised Domain Adaptation. SDM 2021: 576-584 - [i13]Huan Wang, Can Qin, Yulun Zhang, Yun Fu:
Emerging Paradigms of Neural Network Pruning. CoRR abs/2103.06460 (2021) - [i12]Joseph P. Robinson, Can Qin, Yann Henon, Samson Timoner, Yun Fu:
Balancing Biases and Preserving Privacy on Balanced Faces in the Wild. CoRR abs/2103.09118 (2021) - [i11]Huan Wang, Can Qin, Yue Bai, Yun Fu:
Dynamical Isometry: The Missing Ingredient for Neural Network Pruning. CoRR abs/2105.05916 (2021) - [i10]Yizhou Wang, Yue Kang, Can Qin, Yi Xu, Huan Wang, Yulun Zhang, Yun Fu:
Adapting Stepsizes by Momentumized Gradients Improves Optimization and Generalization. CoRR abs/2106.11514 (2021) - [i9]Joseph P. Robinson, Can Qin, Ming Shao, Matthew A. Turk, Rama Chellappa, Yun Fu:
The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces. CoRR abs/2111.00598 (2021) - [i8]Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu:
SLA2P: Self-supervised Anomaly Detection with Adversarial Perturbation. CoRR abs/2111.12896 (2021) - [i7]Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu:
Semi-supervised Domain Adaptive Structure Learning. CoRR abs/2112.06161 (2021) - 2020
- [j1]Yue Wu, Guifeng Mu, Can Qin, Qiguang Miao, Wenping Ma, Xiangrong Zhang:
Semi-Supervised Hyperspectral Image Classification via Spatial-Regulated Self-Training. Remote. Sens. 12(1): 159 (2020) - [c8]Lichen Wang, Yunyu Liu, Can Qin, Gan Sun, Yun Fu:
Dual Relation Semi-Supervised Multi-Label Learning. AAAI 2020: 6227-6234 - [c7]Joseph P. Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, Samson Timoner:
Face Recognition: Too Bias, or Not Too Bias? CVPR Workshops 2020: 1-10 - [c6]Yunyu Liu, Lichen Wang, Yue Bai, Can Qin, Zhengming Ding, Yun Fu:
Generative View-Correlation Adaptation for Semi-supervised Multi-view Learning. ECCV (14) 2020: 318-334 - [i6]Changyu Deng, Can Qin, Wei Lu:
Deep-Learning-Enabled Simulated Annealing for Topology Optimization. CoRR abs/2002.01927 (2020) - [i5]Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu:
Opposite Structure Learning for Semi-supervised Domain Adaptation. CoRR abs/2002.02545 (2020) - [i4]Joseph P. Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, Samson Timoner:
Face Recognition: Too Bias, or Not Too Bias? CoRR abs/2002.06483 (2020) - [i3]Yu Yin, Joseph P. Robinson, Songyao Jiang, Yue Bai, Can Qin, Yun Fu:
SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis. CoRR abs/2012.04111 (2020) - [i2]Huan Wang, Can Qin, Yulun Zhang, Yun Fu:
Neural Pruning via Growing Regularization. CoRR abs/2012.09243 (2020)
2010 – 2019
- 2019
- [c5]Can Qin, Lichen Wang, Yulun Zhang, Yun Fu:
Generatively Inferential Co-Training for Unsupervised Domain Adaptation. ICCV Workshops 2019: 1055-1064 - [c4]Can Qin, Haoxuan You, Lichen Wang, C.-C. Jay Kuo, Yun Fu:
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation. NeurIPS 2019: 7190-7201 - [i1]Can Qin, Haoxuan You, Lichen Wang, C.-C. Jay Kuo, Yun Fu:
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation. CoRR abs/1911.02744 (2019) - 2018
- [c3]Can Qin, Maoguo Gong, Yue Wu, Dayong Tian, Puzhao Zhang:
Efficient Scene Labeling via Sparse Annotations. AAAI Workshops 2018: 194-201 - 2017
- [c2]Shanfeng Wang, Maoguo Gong, Can Qin, Junwei Yang:
A Multi-objective Framework for Location Recommendation Based on User Preference. CIS 2017: 39-43 - [c1]Wenping Ma, Yue Wu, Maoguo Gong, Can Qin, Shanfeng Wang:
Local Probabilistic Matrix Factorization for Personal Recommendation. CIS 2017: 97-101
Coauthor Index
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last updated on 2023-10-31 20:41 CET by the dblp team
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