HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis
Fuente:
arXiv
Saved in:
| Main Authors: | Yin, Xuanhua, Zhang, Dingxin, Yu, Jianhui, Cai, Weidong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Beyond Random Masking: A Dual-Stream Approach for Rotation-Invariant Point Cloud Masked Autoencoders
by: Yin, Xuanhua, et al.
Published: (2025)
by: Yin, Xuanhua, et al.
Published: (2025)
PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose Restoration
by: Zhang, Dingxin, et al.
Published: (2023)
by: Zhang, Dingxin, et al.
Published: (2023)
RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning
by: Su, Kunming, et al.
Published: (2024)
by: Su, Kunming, et al.
Published: (2024)
Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module
by: Zhang, Dingxin, et al.
Published: (2024)
by: Zhang, Dingxin, et al.
Published: (2024)
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learning
by: Wei, Weijie, et al.
Published: (2023)
by: Wei, Weijie, et al.
Published: (2023)
Stealthy Patch-Wise Backdoor Attack in 3D Point Cloud via Curvature Awareness
by: Feng, Yu, et al.
Published: (2025)
by: Feng, Yu, et al.
Published: (2025)
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
by: Zhang, Xiangdong, et al.
Published: (2024)
by: Zhang, Xiangdong, et al.
Published: (2024)
DAP-MAE: Domain-Adaptive Point Cloud Masked Autoencoder for Effective Cross-Domain Learning
by: Gao, Ziqi, et al.
Published: (2025)
by: Gao, Ziqi, et al.
Published: (2025)
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios
by: Lin, Zhiwei, et al.
Published: (2022)
by: Lin, Zhiwei, et al.
Published: (2022)
R-MAE: Regions Meet Masked Autoencoders
by: Nguyen, Duy-Kien, et al.
Published: (2023)
by: Nguyen, Duy-Kien, et al.
Published: (2023)
Rotation-Invariant Transformer for Point Cloud Matching
by: Yu, Hao, et al.
Published: (2023)
by: Yu, Hao, et al.
Published: (2023)
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
by: Jiang, Xueying, et al.
Published: (2024)
by: Jiang, Xueying, et al.
Published: (2024)
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning
by: Liu, Rex, et al.
Published: (2024)
by: Liu, Rex, et al.
Published: (2024)
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
by: Yan, Siming, et al.
Published: (2023)
by: Yan, Siming, et al.
Published: (2023)
MaskLRF: Self-supervised Pretraining via Masked Autoencoding of Local Reference Frames for Rotation-invariant 3D Point Set Analysis
by: Furuya, Takahiko
Published: (2024)
by: Furuya, Takahiko
Published: (2024)
MV2MAE: Multi-View Video Masked Autoencoders
by: Shah, Ketul, et al.
Published: (2024)
by: Shah, Ketul, et al.
Published: (2024)
RIDE: Boosting 3D Object Detection for LiDAR Point Clouds via Rotation-Invariant Analysis
by: Wang, Zhaoxuan, et al.
Published: (2024)
by: Wang, Zhaoxuan, et al.
Published: (2024)
Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation
by: Liu, Jiaming, et al.
Published: (2023)
by: Liu, Jiaming, et al.
Published: (2023)
Exploring Semantic Masked Autoencoder for Self-supervised Point Cloud Understanding
by: Zha, Yixin, et al.
Published: (2025)
by: Zha, Yixin, et al.
Published: (2025)
DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction
by: Li, Yanlong, et al.
Published: (2023)
by: Li, Yanlong, et al.
Published: (2023)
RISurConv: Rotation Invariant Surface Attention-Augmented Convolutions for 3D Point Cloud Classification and Segmentation
by: Zhang, Zhiyuan, et al.
Published: (2024)
by: Zhang, Zhiyuan, et al.
Published: (2024)
Periodic-MAE: Periodic Video Masked Autoencoder for rPPG Estimation
by: Choi, Jiho, et al.
Published: (2025)
by: Choi, Jiho, et al.
Published: (2025)
MultiMAE-DER: Multimodal Masked Autoencoder for Dynamic Emotion Recognition
by: Xiang, Peihao, et al.
Published: (2024)
by: Xiang, Peihao, et al.
Published: (2024)
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization
by: Zhang, Zhimin, et al.
Published: (2024)
by: Zhang, Zhimin, et al.
Published: (2024)
CL-MAE: Curriculum-Learned Masked Autoencoders
by: Madan, Neelu, et al.
Published: (2023)
by: Madan, Neelu, et al.
Published: (2023)
DuGI-MAE: Improving Infrared Mask Autoencoders via Dual-Domain Guidance
by: Xing, Yinghui, et al.
Published: (2025)
by: Xing, Yinghui, et al.
Published: (2025)
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
by: Liang, Feng, et al.
Published: (2022)
by: Liang, Feng, et al.
Published: (2022)
DailyMAE: Towards Pretraining Masked Autoencoders in One Day
by: Wu, Jiantao, et al.
Published: (2024)
by: Wu, Jiantao, et al.
Published: (2024)
LV-MAE: Learning Long Video Representations through Masked-Embedding Autoencoders
by: Naiman, Ilan, et al.
Published: (2025)
by: Naiman, Ilan, et al.
Published: (2025)
$\mathsf{CSMAE~}$:~Cataract Surgical Masked Autoencoder (MAE) based Pre-training
by: Shah, Nisarg A., et al.
Published: (2025)
by: Shah, Nisarg A., et al.
Published: (2025)
Social-MAE: Social Masked Autoencoder for Multi-person Motion Representation Learning
by: Ehsanpour, Mahsa, et al.
Published: (2024)
by: Ehsanpour, Mahsa, et al.
Published: (2024)
i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?
by: Zhang, Kevin, et al.
Published: (2022)
by: Zhang, Kevin, et al.
Published: (2022)
SCE-MAE: Selective Correspondence Enhancement with Masked Autoencoder for Self-Supervised Landmark Estimation
by: Yin, Kejia, et al.
Published: (2024)
by: Yin, Kejia, et al.
Published: (2024)
PAME: Self-Supervised Masked Autoencoder for No-Reference Point Cloud Quality Assessment
by: Shan, Ziyu, et al.
Published: (2024)
by: Shan, Ziyu, et al.
Published: (2024)
CrossVideoMAE: Self-Supervised Image-Video Representation Learning with Masked Autoencoders
by: Ahamed, Shihab Aaqil, et al.
Published: (2025)
by: Ahamed, Shihab Aaqil, et al.
Published: (2025)
AccelAes: Accelerating Diffusion Transformers for Training-Free Aesthetic-Enhanced Image Generation
by: Yin, Xuanhua, et al.
Published: (2026)
by: Yin, Xuanhua, et al.
Published: (2026)
CryoMAE: Few-Shot Cryo-EM Particle Picking with Masked Autoencoders
by: Xu, Chentianye, et al.
Published: (2024)
by: Xu, Chentianye, et al.
Published: (2024)
Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning
by: Ren, Bin, et al.
Published: (2024)
by: Ren, Bin, et al.
Published: (2024)
AU-vMAE: Knowledge-Guide Action Units Detection via Video Masked Autoencoder
by: Jin, Qiaoqiao, et al.
Published: (2024)
by: Jin, Qiaoqiao, et al.
Published: (2024)
MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder
by: Erdur, Ayhan Can, et al.
Published: (2025)
by: Erdur, Ayhan Can, et al.
Published: (2025)
Similar Items
-
Beyond Random Masking: A Dual-Stream Approach for Rotation-Invariant Point Cloud Masked Autoencoders
by: Yin, Xuanhua, et al.
Published: (2025) -
PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose Restoration
by: Zhang, Dingxin, et al.
Published: (2023) -
RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning
by: Su, Kunming, et al.
Published: (2024) -
Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module
by: Zhang, Dingxin, et al.
Published: (2024) -
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learning
by: Wei, Weijie, et al.
Published: (2023)