MAE是一种使用自监督预训练策略的ViT,通过遮蔽输入图像中的补丁,然后预测缺失区域进行子监督与训练。尽管该方法既简单又有效,但 MAE 预训练目标目前仅限于单一模态——RGB 图像——限制了在通常呈现多模态信息的实际场景中的应用和性能。 ...
Masked autoencoder (MAE) is a self-supervised learning method that outperforms supervised learning methods without relying on large-scale databases. The MAE can improve the feature extraction ability of the model effectively. The multi-scale convolution strategy can expand the receptive field and ...
MAE是一种使用自监督预训练策略的ViT,通过遮蔽输入图像中的补丁,然后预测缺失区域进行子监督的与训练。尽管该方法既简单又有效,但 MAE 预训练目标目前仅限于单一模态——RGB 图像——限制了在通常呈现多模态信息的实际场景中的应用和性能。 在新论文 MultiMAE: Multi-modal Multi-task Masked Autoencoders 中,来自...
Masked autoencoders (MAEs) are a self-supervised pretraining strategy for vision transformers (ViTs) that masks-out patches in an input image and then predicts the missing regions. Although the approach is both simple and effective, the MAE...
mv2mae: multi-view video masked autoencoders 1. 解释什么是mv2mae mv2mae(Multi-View Video Masked Autoencoders)是一种基于多视角视频数据的掩码自编码器模型。它结合了多视角视频和掩码自编码器的优势,旨在从多视角视频数据中学习更丰富的视觉表示。 2. 阐述multi-view video的含义及其在mv2mae中的作用 ...
Automatically labeling trajectories of multiple agents is key to behavioral analyses but usually requires a large amount of manual annotations. This also a
We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB image (hence "multi-modal"), and II...
However, it still remains an open question on how to exploit masked autoencoding for learning 3D representations of irregular point clouds. In this paper, we propose Point-M2AE, a strong Multi-scale MAE pre-training framework for hierarchical self-supervised learning of 3D point clouds. Unlike ...
For this purpose, we propose a novel self-supervised masked autoencoder for multiagent trajectories to effectively learn from only a few labeled sequences. Our approach builds upon a factorized transformer architecture for multiagent trajectory data and employs a masking scheme on the level of ...
Resource-Efficient Multiview Perception: Integrating Semantic Masking with Masked Autoencoders 7 Oct 2024 · Kosta Dakic, Kanchana Thilakarathna, Rodrigo N. Calheiros, Teng Joon Lim · Edit social preview Multiview systems have become a key technology in modern computer vision, offering advanced ...