Da-Wei Zhou

According to our database, Da-Wei Zhou authored at least 31 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

TV100: a TV series dataset that pre-trained CLIP has not seen.

Da-Wei Zhou, Zhi-Hong Qi, Han-Jia Ye, De-Chuan Zhan

Frontiers Comput. Sci., October, 2024

Contextualizing Meta-Learning via Learning to Decompose.

Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning.

Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan

CoRR, 2024

Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning.

Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao, Han-Jia Ye, De-Chuan Zhan

CoRR, 2024

Parrot: Multilingual Visual Instruction Tuning.

Hai-Long Sun, Da-Wei Zhou, Yang Li, Shiyin Lu, Chao Yi, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye

CoRR, 2024

Continual Learning with Pre-Trained Models: A Survey.

Da-Wei Zhou, Hai-Long Sun, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning.

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning.

Da-Wei Zhou, Hai-Long Sun, Han-Jia Ye, De-Chuan Zhan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.

Da-Wei Zhou, Han-Jia Ye, Liang Ma, Di Xie, Shiliang Pu, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

PyCIL: a Python toolbox for class-incremental learning.

Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, De-Chuan Zhan

Sci. China Inf. Sci., September, 2023

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling.

Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang, Jian Yang

IEEE Trans. Knowl. Data Eng., April, 2023

RF-Badge: Vital Sign-Based Authentication via RFID Tag Array on Badges.

Jingyi Ning, Lei Xie, Chuyu Wang, Yanling Bu, Fengyuan Xu, Da-Wei Zhou, Sanglu Lu, Baoliu Ye

IEEE Trans. Mob. Comput., 2023

PILOT: A Pre-Trained Model-Based Continual Learning Toolbox.

Hai-Long Sun, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

CoRR, 2023

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data.

Qi-Wei Wang, Hongyu Lu, Yu Chen, Da-Wei Zhou, De-Chuan Zhan, Ming Chen, Han-Jia Ye

CoRR, 2023

Learning without Forgetting for Vision-Language Models.

Da-Wei Zhou, Yuanhan Zhang, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

Deep Class-Incremental Learning: A Survey.

Da-Wei Zhou, Qi-Wei Wang, Zhi-Hong Qi, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration.

Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Preserving Locality in Vision Transformers for Class Incremental Learning.

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion.

Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning.

Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning to Classify With Incremental New Class.

Da-Wei Zhou, Yang Yang, De-Chuan Zhan

IEEE Trans. Neural Networks Learn. Syst., 2022

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

CoRR, 2022

Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation.

Yi-Kai Zhang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

FOSTER: Feature Boosting and Compression for Class-Incremental Learning.

Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Computer Vision - ECCV 2022, 2022

Forward Compatible Few-Shot Class-Incremental Learning.

Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Contextualizing Multiple Tasks via Learning to Decompose.

Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan

CoRR, 2021

Detecting Sequentially Novel Classes with Stable Generalization Ability.

Da-Wei Zhou, Yang Yang, De-Chuan Zhan

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Co-Transport for Class-Incremental Learning.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Learning Placeholders for Open-Set Recognition.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability.

Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019