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2020 – today
- 2024
[j17]Yimin Xu, Mingbao Lin, Hong Yang, Fei Chao
, Rongrong Ji:
Shadow-aware dynamic convolution for shadow removal. Pattern Recognit. 146: 109969 (2024)- [c32]Yanjing Li, Sheng Xu, Mingbao Lin, Xianbin Cao, Chuanjian Liu, Xiao Sun, Baochang Zhang:
Bi-ViT: Pushing the Limit of Vision Transformer Quantization. AAAI 2024: 3243-3251 - [c31]Jingjing Xie, Yuxin Zhang, Mingbao Lin, Zhihang Lin, Liujuan Cao, Rongrong Ji:
UniPTS: A Unified Framework for Proficient Post-Training Sparsity. CVPR 2024: 5746-5755 - [c30]Zhihang Lin, Mingbao Lin, Meng Zhao, Rongrong Ji:
AccDiffusion: An Accurate Method for Higher-Resolution Image Generation. ECCV (6) 2024: 38-53 - [c29]Jiahao Ying, Mingbao Lin, Yixin Cao, Wei Tang, Bo Wang, Qianru Sun, Xuanjing Huang, Shuicheng Yan:
LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement. EMNLP (Findings) 2024: 11185-11208 - [c28]Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji:
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs. ICLR 2024 - [c27]Sheng Xu, Mingze Wang, Yanjing Li, Mingbao Lin, Baochang Zhang, David S. Doermann, Xiao Sun:
Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement. ICML 2024 - [c26]Jingjing Xie, Yuxin Zhang, Mingbao Lin, Liujuan Cao, Rongrong Ji:
Advancing Multimodal Large Language Models with Quantization-Aware Scale Learning for Efficient Adaptation. ACM Multimedia 2024: 10582-10591 - [i67]Mingbao Lin, Zhihang Lin, Wengyi Zhan, Liujuan Cao, Rongrong Ji:
CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation Method. CoRR abs/2404.15141 (2024) - [i66]Ziyue Zhang, Mingbao Lin, Rongrong Ji:
ObjectAdd: Adding Objects into Image via a Training-Free Diffusion Modification Fashion. CoRR abs/2404.17230 (2024) - [i65]Zhihang Lin, Mingbao Lin, Luxi Lin, Rongrong Ji:
Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference. CoRR abs/2405.05803 (2024) - [i64]Jingjing Xie, Yuxin Zhang, Mingbao Lin, Zhihang Lin, Liujuan Cao, Rongrong Ji:
UniPTS: A Unified Framework for Proficient Post-Training Sparsity. CoRR abs/2405.18810 (2024) - [i63]Wenhao Li, Mingbao Lin, Yunshan Zhong, Shuicheng Yan, Rongrong Ji:
UIO-LLMs: Unbiased Incremental Optimization for Long-Context LLMs. CoRR abs/2406.18173 (2024) - [i62]Jiahao Ying, Mingbao Lin, Yixin Cao, Wei Tang, Bo Wang, Qianru Sun, Xuanjing Huang, Shuicheng Yan:
LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement. CoRR abs/2407.00497 (2024) - [i61]Wengyi Zhan, Mingbao Lin, Chia-Wen Lin, Rongrong Ji:
AnySR: Realizing Image Super-Resolution as Any-Scale, Any-Resource. CoRR abs/2407.04241 (2024) - [i60]Zhihang Lin, Mingbao Lin, Meng Zhao, Rongrong Ji:
AccDiffusion: An Accurate Method for Higher-Resolution Image Generation. CoRR abs/2407.10738 (2024) - [i59]Pengfei Jiang, Mingbao Lin, Fei Chao, Rongrong Ji:
Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing. CoRR abs/2407.17847 (2024) - [i58]Jingjing Xie, Yuxin Zhang, Mingbao Lin, Liujuan Cao, Rongrong Ji:
Advancing Multimodal Large Language Models with Quantization-Aware Scale Learning for Efficient Adaptation. CoRR abs/2408.03735 (2024) - [i57]Ziyue Zhang, Mingbao Lin, Shuicheng Yan, Rongrong Ji:
EasyInv: Toward Fast and Better DDIM Inversion. CoRR abs/2408.05159 (2024) - 2023
- [j16]Mingbao Lin, Mengzhao Chen, Yuxin Zhang, Chunhua Shen, Rongrong Ji, Liujuan Cao:
Super Vision Transformer. Int. J. Comput. Vis. 131(12): 3136-3151 (2023) - [j15]Boyu Yang, Mingbao Lin, Yunxiao Zhang, Binghao Liu, Xiaodan Liang, Rongrong Ji, Qixiang Ye:
Dynamic Support Network for Few-Shot Class Incremental Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2945-2951 (2023) - [j14]Mingbao Lin, Yuxin Zhang, Yuchao Li, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Yonghong Tian, Rongrong Ji:
1xN Pattern for Pruning Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 3999-4008 (2023) - [j13]Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Fei Chao, Chia-Wen Lin, Ling Shao:
SiMaN: Sign-to-Magnitude Network Binarization. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 6277-6288 (2023) - [j12]Mingbao Lin, Bohong Chen, Fei Chao, Rongrong Ji:
Training Compact CNNs for Image Classification Using Dynamic-Coded Filter Fusion. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10478-10487 (2023) - [j11]Bohong Chen, Mingbao Lin, Rongrong Ji, Liujuan Cao:
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 11108-11119 (2023) - [j10]Yuxin Zhang, Mingbao Lin, Yunshan Zhong, Fei Chao, Rongrong Ji:
Lottery Jackpots Exist in Pre-Trained Models. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14990-15004 (2023) - [j9]Shaojie Li, Mingbao Lin, Yan Wang, Fei Chao, Ling Shao, Rongrong Ji:
Learning Efficient GANs for Image Translation via Differentiable Masks and Co-Attention Distillation. IEEE Trans. Multim. 25: 3180-3189 (2023) - [j8]Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Yongjian Wu, Yonghong Tian, Rongrong Ji:
Carrying Out CNN Channel Pruning in a White Box. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7946-7955 (2023) - [j7]Shaojie Li, Mingbao Lin, Yan Wang, Yongjian Wu, Yonghong Tian, Ling Shao, Rongrong Ji:
Distilling a Powerful Student Model via Online Knowledge Distillation. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8743-8752 (2023) - [j6]Mingbao Lin, Liujuan Cao, Yuxin Zhang, Ling Shao, Chia-Wen Lin, Rongrong Ji:
Pruning Networks With Cross-Layer Ranking & k-Reciprocal Nearest Filters. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9139-9148 (2023) - [c25]Mingrui Wu, Jiaxin Gu, Yunhang Shen, Mingbao Lin, Chao Chen, Xiaoshuai Sun:
End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation. AAAI 2023: 2839-2846 - [c24]Mengzhao Chen, Mingbao Lin, Ke Li, Yunhang Shen, Yongjian Wu, Fei Chao, Rongrong Ji:
CF-ViT: A General Coarse-to-Fine Method for Vision Transformer. AAAI 2023: 7042-7052 - [c23]Sheng Xu, Yanjing Li, Teli Ma, Mingbao Lin, Hao Dong, Baochang Zhang, Peng Gao, Jinhu Lu:
Resilient Binary Neural Network. AAAI 2023: 10620-10628 - [c22]Sheng Xu, Yanjing Li, Mingbao Lin, Peng Gao, Guodong Guo, Jinhu Lü, Baochang Zhang:
Q-DETR: An Efficient Low-Bit Quantized Detection Transformer. CVPR 2023: 3842-3851 - [c21]Tie Hu, Mingbao Lin, Lizhou You, Fei Chao, Rongrong Ji:
Discriminator-Cooperated Feature Map Distillation for GAN Compression. CVPR 2023: 20351-20360 - [c20]Yanjing Li, Sheng Xu, Mingbao Lin, Jihao Yin, Baochang Zhang, Xianbin Cao:
Representation Disparity-aware Distillation for 3D Object Detection. ICCV 2023: 6692-6701 - [c19]Mengzhao Chen, Wenqi Shao, Peng Xu, Mingbao Lin, Kaipeng Zhang, Fei Chao, Rongrong Ji, Yu Qiao, Ping Luo:
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers. ICCV 2023: 17118-17128 - [c18]Mengzhao Chen, Mingbao Lin, Zhihang Lin, Yuxin Zhang, Fei Chao, Rongrong Ji:
SMMix: Self-Motivated Image Mixing for Vision Transformers. ICCV 2023: 17214-17224 - [c17]Yuxin Zhang, Mingbao Lin, Xunchao Li, Han Liu, Guozhi Wang, Fei Chao, Shuai Ren, Yafei Wen, Xiaoxin Chen, Rongrong Ji:
Real-Time Image Demoiréing on Mobile Devices. ICLR 2023 - [c16]Yuxin Zhang, Yiting Luo, Mingbao Lin, Yunshan Zhong, Jingjing Xie, Fei Chao, Rongrong Ji:
Bi-directional Masks for Efficient N: M Sparse Training. ICML 2023: 41488-41497 - [i56]Ziran Qin, Mingbao Lin, Weiyao Lin:
Low-Rank Winograd Transformation for 3D Convolutional Neural Networks. CoRR abs/2301.11180 (2023) - [i55]Sheng Xu, Yanjing Li, Teli Ma, Mingbao Lin, Hao Dong, Baochang Zhang, Peng Gao, Jinhu Lv:
Resilient Binary Neural Network. CoRR abs/2302.00956 (2023) - [i54]Yuxin Zhang, Mingbao Lin, Xunchao Li, Han Liu, Guozhi Wang, Fei Chao, Shuai Ren, Yafei Wen, Xiaoxin Chen, Rongrong Ji:
Real-Time Image Demoireing on Mobile Devices. CoRR abs/2302.02184 (2023) - [i53]Yuxin Zhang, Yiting Luo, Mingbao Lin, Yunshan Zhong, Jingjing Xie, Fei Chao, Rongrong Ji:
Bi-directional Masks for Efficient N: M Sparse Training. CoRR abs/2302.06058 (2023) - [i52]Sheng Xu, Yanjing Li, Mingbao Lin, Peng Gao, Guodong Guo, Jinhu Lu, Baochang Zhang:
Q-DETR: An Efficient Low-Bit Quantized Detection Transformer. CoRR abs/2304.00253 (2023) - [i51]Yunshan Zhong, Mingbao Lin, Jingjing Xie, Yuxin Zhang, Fei Chao, Rongrong Ji:
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks. CoRR abs/2305.05888 (2023) - [i50]Yunshan Zhong, Mingbao Lin, Yuyao Zhou, Mengzhao Chen, Yuxin Zhang, Fei Chao, Rongrong Ji:
MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization. CoRR abs/2305.08117 (2023) - [i49]Yanjing Li, Sheng Xu, Mingbao Lin, Xianbin Cao, Chuanjian Liu, Xiao Sun, Baochang Zhang:
Bi-ViT: Pushing the Limit of Vision Transformer Quantization. CoRR abs/2305.12354 (2023) - [i48]Mengzhao Chen, Wenqi Shao, Peng Xu, Mingbao Lin, Kaipeng Zhang, Fei Chao, Rongrong Ji, Yu Qiao, Ping Luo:
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers. CoRR abs/2305.17997 (2023) - [i47]Yuxin Zhang, Mingbao Lin, Yunshan Zhong, Mengzhao Chen, Fei Chao, Rongrong Ji:
Spatial Re-parameterization for N: M Sparsity. CoRR abs/2306.05612 (2023) - [i46]Junru Lu, Siyu An, Mingbao Lin, Gabriele Pergola, Yulan He, Di Yin, Xing Sun, Yunsheng Wu:
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation. CoRR abs/2308.08239 (2023) - [i45]Yanjing Li, Sheng Xu, Mingbao Lin, Jihao Yin, Baochang Zhang, Xianbin Cao:
Representation Disparity-aware Distillation for 3D Object Detection. CoRR abs/2308.10308 (2023) - [i44]Xiujun Shu, Wei Wen, Liangsheng Xu, Mingbao Lin, Ruizhi Qiao, Taian Guo, Hanjun Li, Bei Gan, Xiao Wang, Xing Sun:
Unified and Dynamic Graph for Temporal Character Grouping in Long Videos. CoRR abs/2308.14105 (2023) - [i43]Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji:
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs. CoRR abs/2310.08915 (2023) - [i42]Yunshan Zhong, Jiawei Hu, Mingbao Lin, Mengzhao Chen, Rongrong Ji:
I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization. CoRR abs/2311.10126 (2023) - [i41]Lirui Zhao, Yuxin Zhang, Mingbao Lin, Fei Chao, Rongrong Ji:
Boosting the Cross-Architecture Generalization of Dataset Distillation through an Empirical Study. CoRR abs/2312.05598 (2023) - 2022
- [j5]Mingbao Lin, Rongrong Ji, Xiaoshuai Sun, Baochang Zhang, Feiyue Huang, Yonghong Tian, Dacheng Tao:
Fast Class-Wise Updating for Online Hashing. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2453-2467 (2022) - [j4]Mingbao Lin, Liujuan Cao, Shaojie Li, Qixiang Ye, Yonghong Tian, Jianzhuang Liu, Qi Tian, Rongrong Ji:
Filter Sketch for Network Pruning. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7091-7100 (2022) - [j3]Mingbao Lin, Rongrong Ji, Shaojie Li, Yan Wang, Yongjian Wu, Feiyue Huang, Qixiang Ye:
Network Pruning Using Adaptive Exemplar Filters. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7357-7366 (2022) - [c15]Yunshan Zhong, Mingbao Lin, Gongrui Nan, Jianzhuang Liu, Baochang Zhang, Yonghong Tian, Rongrong Ji:
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization. CVPR 2022: 12329-12338 - [c14]Yunshan Zhong, Mingbao Lin, Xunchao Li, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji:
Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks. ECCV (18) 2022: 1-18 - [c13]Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Liujuan Cao:
Knowledge Condensation Distillation. ECCV (11) 2022: 19-35 - [c12]Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji:
Fine-grained Data Distribution Alignment for Post-Training Quantization. ECCV (11) 2022: 70-86 - [c11]Bohong Chen, Mingbao Lin, Kekai Sheng, Mengdan Zhang, Peixian Chen, Ke Li, Liujuan Cao, Rongrong Ji:
ARM: Any-Time Super-Resolution Method. ECCV (19) 2022: 254-270 - [c10]Chaoyang Zhu, Yiyi Zhou, Yunhang Shen, Gen Luo, Xingjia Pan, Mingbao Lin, Chao Chen, Liujuan Cao, Xiaoshuai Sun, Rongrong Ji:
SeqTR: A Simple Yet Universal Network for Visual Grounding. ECCV (35) 2022: 598-615 - [c9]Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji:
Learning Best Combination for Efficient N: M Sparsity. NeurIPS 2022 - [i40]Yuxin Zhang, Mingbao Lin, Mengzhao Chen, Zihan Xu, Fei Chao, Yunhang Shen, Ke Li, Yongjian Wu, Rongrong Ji:
Optimizing Gradient-driven Criteria in Network Sparsity: Gradient is All You Need. CoRR abs/2201.12826 (2022) - [i39]Mingbao Lin, Liujuan Cao, Yuxin Zhang, Ling Shao, Chia-Wen Lin, Rongrong Ji:
Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters. CoRR abs/2202.07190 (2022) - [i38]Mengzhao Chen, Mingbao Lin, Ke Li, Yunhang Shen, Yongjian Wu, Fei Chao, Rongrong Ji:
Coarse-to-Fine Vision Transformer. CoRR abs/2203.03821 (2022) - [i37]Yunshan Zhong, Mingbao Lin, Xunchao Li, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji:
Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks. CoRR abs/2203.03844 (2022) - [i36]Bohong Chen, Mingbao Lin, Kekai Sheng, Mengdan Zhang, Peixian Chen, Ke Li, Liujuan Cao, Rongrong Ji:
ARM: Any-Time Super-Resolution Method. CoRR abs/2203.10812 (2022) - [i35]Chaoyang Zhu, Yiyi Zhou, Yunhang Shen, Gen Luo, Xingjia Pan, Mingbao Lin, Chao Chen, Liujuan Cao, Xiaoshuai Sun, Rongrong Ji:
SeqTR: A Simple yet Universal Network for Visual Grounding. CoRR abs/2203.16265 (2022) - [i34]Mingrui Wu, Jiaxin Gu, Yunhang Shen, Mingbao Lin, Chao Chen, Xiaoshuai Sun, Rongrong Ji:
End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation. CoRR abs/2204.03541 (2022) - [i33]Yimin Xu, Mingbao Lin, Hong Yang, Ke Li, Yunhang Shen, Fei Chao, Rongrong Ji:
Shadow-Aware Dynamic Convolution for Shadow Removal. CoRR abs/2205.04908 (2022) - [i32]Mingbao Lin, Mengzhao Chen, Yuxin Zhang, Ke Li, Yunhang Shen, Chunhua Shen, Rongrong Ji:
Super Vision Transformer. CoRR abs/2205.11397 (2022) - [i31]Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji:
Learning Best Combination for Efficient N: M Sparsity. CoRR abs/2206.06662 (2022) - [i30]Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Liujuan Cao:
Knowledge Condensation Distillation. CoRR abs/2207.05409 (2022) - [i29]Hong Yang, Gongrui Nan, Mingbao Lin, Fei Chao, Yunhang Shen, Ke Li, Rongrong Ji:
LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal. CoRR abs/2208.13039 (2022) - [i28]Yunshan Zhong, Mingbao Lin, Yuxin Zhang, Gongrui Nan, Fei Chao, Rongrong Ji:
Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training. CoRR abs/2211.08544 (2022) - [i27]Yunshan Zhong, Mingbao Lin, Lizhou You, Yuxin Zhang, Luoqi Liu, Rongrong Ji:
Shadow Removal by High-Quality Shadow Synthesis. CoRR abs/2212.04108 (2022) - [i26]Lizhou You, Mingbao Lin, Tie Hu, Fei Chao, Rongrong Ji:
Exploring Content Relationships for Distilling Efficient GANs. CoRR abs/2212.11091 (2022) - [i25]Mengzhao Chen, Mingbao Lin, Zhihang Lin, Yuxin Zhang, Fei Chao, Rongrong Ji:
SMMix: Self-Motivated Image Mixing for Vision Transformers. CoRR abs/2212.12977 (2022) - [i24]Tie Hu, Mingbao Lin, Lizhou You, Fei Chao, Rongrong Ji:
Discriminator-Cooperated Feature Map Distillation for GAN Compression. CoRR abs/2212.14169 (2022) - 2021
- [c8]Zihan Xu, Mingbao Lin, Jianzhuang Liu, Jie Chen, Ling Shao, Yue Gao, Yonghong Tian, Rongrong Ji:
ReCU: Reviving the Dead Weights in Binary Neural Networks. ICCV 2021: 5178-5188 - [i23]Mingbao Lin, Rongrong Ji, Shaojie Li, Yan Wang, Yongjian Wu, Feiyue Huang, Qixiang Ye:
Non-Parametric Adaptive Network Pruning. CoRR abs/2101.07985 (2021) - [i22]Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Fei Chao, Mingliang Xu, Chia-Wen Lin, Ling Shao:
SiMaN: Sign-to-Magnitude Network Binarization. CoRR abs/2102.07981 (2021) - [i21]Zihan Xu, Mingbao Lin, Jianzhuang Liu, Jie Chen, Ling Shao, Yue Gao, Yonghong Tian, Rongrong Ji:
ReCU: Reviving the Dead Weights in Binary Neural Networks. CoRR abs/2103.12369 (2021) - [i20]Shaojie Li, Mingbao Lin, Yan Wang, Feiyue Huang, Yongjian Wu, Yonghong Tian, Ling Shao, Rongrong Ji:
Distilling a Powerful Student Model via Online Knowledge Distillation. CoRR abs/2103.14473 (2021) - [i19]Boyu Yang, Mingbao Lin, Binghao Liu, Mengying Fu, Chang Liu, Rongrong Ji, Qixiang Ye:
Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning. CoRR abs/2104.02281 (2021) - [i18]Yuxin Zhang, Mingbao Lin, Fei Chao, Yan Wang, Yongjian Wu, Feiyue Huang, Mingliang Xu, Yonghong Tian, Rongrong Ji:
Lottery Jackpots Exist in Pre-trained Models. CoRR abs/2104.08700 (2021) - [i17]Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji:
Carrying out CNN Channel Pruning in a White Box. CoRR abs/2104.11883 (2021) - [i16]Mingbao Lin, Yuchao Li, Yuxin Zhang, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji:
1×N Block Pattern for Network Sparsity. CoRR abs/2105.14713 (2021) - [i15]Mingbao Lin, Rongrong Ji, Bohong Chen, Fei Chao, Jianzhuang Liu, Wei Zeng, Yonghong Tian, Qi Tian:
Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion. CoRR abs/2107.06916 (2021) - [i14]Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Feiyue Huang, Rongrong Ji:
Fine-grained Data Distribution Alignment for Post-Training Quantization. CoRR abs/2109.04186 (2021) - [i13]Bohong Chen, Mingbao Lin, Liujuan Cao, Jianzhuang Liu, Qixiang Ye, Baochang Zhang, Wei Zeng, Yonghong Tian, Rongrong Ji:
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training. CoRR abs/2109.05432 (2021) - [i12]Yunshan Zhong, Mingbao Lin, Gongrui Nan, Jianzhuang Liu, Baochang Zhang, Yonghong Tian, Rongrong Ji:
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization. CoRR abs/2111.09136 (2021) - 2020
- [j2]Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Shen Chen, Qi Tian:
Hadamard Matrix Guided Online Hashing. Int. J. Comput. Vis. 128(8): 2279-2306 (2020) - [j1]Mingbao Lin, Rongrong Ji, Shen Chen, Xiaoshuai Sun, Chia-Wen Lin:
Similarity-Preserving Linkage Hashing for Online Image Retrieval. IEEE Trans. Image Process. 29: 5289-5300 (2020) - [c7]Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, Ling Shao:
HRank: Filter Pruning Using High-Rank Feature Map. CVPR 2020: 1526-1535 - [c6]Mingbao Lin, Rongrong Ji, Yuxin Zhang, Baochang Zhang, Yongjian Wu, Yonghong Tian:
Channel Pruning via Automatic Structure Search. IJCAI 2020: 673-679 - [c5]Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin:
Rotated Binary Neural Network. NeurIPS 2020 - [i11]Mingbao Lin, Rongrong Ji, Shaojie Li, Qixiang Ye, Yonghong Tian, Jianzhuang Liu, Qi Tian:
Filter Sketch for Network Pruning. CoRR abs/2001.08514 (2020) - [i10]Mingbao Lin, Rongrong Ji, Yuxin Zhang, Baochang Zhang, Yongjian Wu, Yonghong Tian:
Channel Pruning via Automatic Structure Search. CoRR abs/2001.08565 (2020) - [i9]Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, Ling Shao:
HRank: Filter Pruning using High-Rank Feature Map. CoRR abs/2002.10179 (2020) - [i8]Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin:
Rotated Binary Neural Network. CoRR abs/2009.13055 (2020) - [i7]Shaojie Li, Mingbao Lin, Yan Wang, Mingliang Xu, Feiyue Huang, Yongjian Wu, Ling Shao, Rongrong Ji:
Learning Efficient GANs using Differentiable Masks and co-Attention Distillation. CoRR abs/2011.08382 (2020) - [i6]Mingbao Lin, Rongrong Ji, Xiaoshuai Sun, Baochang Zhang, Feiyue Huang, Yonghong Tian, Dacheng Tao:
Fast Class-wise Updating for Online Hashing. CoRR abs/2012.00318 (2020)
2010 – 2019
- 2019
- [c4]Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Yongjian Wu, Yunsheng Wu:
Towards Optimal Discrete Online Hashing with Balanced Similarity. AAAI 2019: 8722-8729 - [i5]Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Yongjian Wu, Yunsheng Wu:
Towards Optimal Discrete Online Hashing with Balanced Similarity. CoRR abs/1901.10185 (2019) - [i4]Mingbao Lin, Rongrong Ji, Hong Liu, Yongjian Wu:
Supervised Online Hashing via Hadamard Codebook Learning. CoRR abs/1905.03694 (2019) - [i3]Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Shen Chen, Qi Tian:
Hadamard Matrix Guided Online Hashing. CoRR abs/1905.04454 (2019) - [i2]Mingbao Lin, Rongrong Ji, Shen Chen, Feng Zheng, Xiaoshuai Sun, Baochang Zhang, Liujuan Cao, Guodong Guo, Feiyue Huang:
Supervised Online Hashing via Similarity Distribution Learning. CoRR abs/1905.13382 (2019) - [i1]Shen Chen, Liujuan Cao, Mingbao Lin, Yan Wang, Xiaoshuai Sun, Chenglin Wu, Jingfei Qiu, Rongrong Ji:
Hadamard Codebook Based Deep Hashing. CoRR abs/1910.09182 (2019) - 2018
- [c3]Hong Liu, Mingbao Lin, Shengchuan Zhang, Yongjian Wu, Feiyue Huang, Rongrong Ji:
Dense Auto-Encoder Hashing for Robust Cross-Modality Retrieval. ACM Multimedia 2018: 1589-1597 - [c2]Mingbao Lin, Rongrong Ji, Hong Liu, Yongjian Wu:
Supervised Online Hashing via Hadamard Codebook Learning. ACM Multimedia 2018: 1635-1643 - 2017
- [c1]Mingbao Lin, Xianming Lin, Yunhang Shen, Rongrong Ji:
Sensitive Information Detection on Cyber-Space. ICIG (3) 2017: 496-504
Coauthor Index
[j17] [c31] [c30] [c28] [c26] [i67] [i66] [i65] [i64] [i63] [i61] [i60] [i59] [i58] [i57] [j16] [j15] [j14] [j13] [j12] [j11] [j10] [j9] [j8] [j7] [j6] [c24] [c21] [c19] [c18] [c17] [c16] [i54] [i53] [i51] [i50] [i48] [i47] [i43] [i42] [i41] [j5] [j4] [j3] [c15] [c14] [c12] [c11] [c10] [c9] [i40] [i39] [i38] [i37] [i36] [i35] [i34] [i33] [i32] [i31] [i29] [i28] [i27] [i26] [i25] [i24] [c8] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [j2] [j1] [c7] [c6] [c5] [i11] [i10] [i9] [i8] [i7] [i6] [c4] [i5] [i4] [i3] [i2] [i1] [c3] [c2] [c1]
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