Xingbin Liu — accepted AI-conference papers

2024

Exploring Target Representations for Masked Autoencoders

xingbin liu, Jinghao Zhou, Tao Kong, Xianming Lin, Rongrong Ji

ICLR 2024poster

Masked autoencoders have become popular training paradigms for self-supervised visual representation learning. These models randomly mask a portion of the input and reconstruct the masked portion according to assigned target representations. In this paper, we show that a careful choice of the target…

Cited by 49 Source ↗PDF ↗code ↗Scholar ↗

2023

Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods

Ya Jing, Xuelin Zhu, Xingbin Liu, Qie Sima, Taozheng Yang, Yunhai Feng +1

IROS 2023poster

Visual pre-training with large-scale real-world data has made great progress in recent years, showing great potential in robot learning with pixel observations. However, the recipes of visual pre-training for robot manipulation tasks are yet to be built. In this paper, we thoroughly investigate the…

Cited by 16 Source ↗code ↗Scholar ↗