The following publications are possibly variants of this publication:
- Swin MAE: Masked autoencoders for small datasetsZi'an Xu, Yin Dai, Fayu Liu, Weibing Chen, Yue Liu, Lifu Shi, Sheng Liu, Yuhang Zhou. cbm, 161:107037, July 2023. [doi]
- Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked AutoencodersJie Cheng, Xiaodong Mei 0001, Ming Liu. iccv 2023: 8645-8655 [doi]
- BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving ScenariosZhiwei Lin, Yongtao Wang, Shengxiang Qi, Nan Dong, Ming-Hsuan Yang 0001. AAAI 2024: 3531-3539 [doi]
- Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-trainingZiyu Guo, Renrui Zhang, Longtian Qiu, Xianzhi Li, Pheng-Ann Heng. IJCAI 2023: 791-799 [doi]
- Flow-MAE: Leveraging Masked AutoEncoder for Accurate, Efficient and Robust Malicious Traffic ClassificationZijun Hang, Yuliang Lu, YongJie Wang, Yi Xie. raid 2023: 297-314 [doi]
- MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression RecognitionLicai Sun, Zheng Lian, Bin Liu, Jianhua Tao. mm 2023: 6110-6121 [doi]
- GAF-MAE: A Self-Supervised Automatic Modulation Classification Method Based on Gramian Angular Field and Masked AutoencoderYunhao Shi, Hua Xu, Yue Zhang, Zisen Qi, Dan Wang. tccn, 10(1):94-106, February 2024. [doi]
- MAE-NIR: A masked autoencoder that enhances near-infrared spectral data to predict soil propertiesMidi Wan, Taiyu Yan, Guoxia Xu, Aibing Liu, Yangbin Zhou, Hao Wang, Xiu Jin. cea, 215:108427, December 2023. [doi]