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cs.CV2023
Self-supervised Learning by View Synthesis
Shaoteng Liu, Xiangyu Zhang, Tao Hu +1
We present view-synthesis autoencoders (VSA) in this paper, which is a self-supervised learning framework designed for vision transformers. Different from traditional 2D pretrainin…
cs.CV2022★ 1 cited
Understanding Masked Image Modeling via Learning Occlusion Invariant Feature
Xiangwen Kong, Xiangyu Zhang
Recently, Masked Image Modeling (MIM) achieves great success in self-supervised visual recognition. However, as a reconstruction-based framework, it is still an open question to un…
cs.CV2022
Revisiting the Critical Factors of Augmentation-Invariant Representation Learning
Junqiang Huang, Xiangwen Kong, Xiangyu Zhang
We focus on better understanding the critical factors of augmentation-invariant representation learning. We revisit MoCo v2 and BYOL and try to prove the authenticity of the follow…