Apr 24, 2020 · Self-supervised representation learning has achieved impressive results in recent years, with experiments primarily coming on ImageNet or other ...
We evaluate and analyze multiple self-supervised learning techniques (Rotation[15],. Instance Discrimination[54] and Jigsaw[34]) on the broadest benchmark yet ...
Nov 13, 2020 · We experiment with several popular methods on an unprecedented variety of domains. We discover, among other findings, that Rotation is the most semantically ...
This is the pytorch code for the paper: Extending and Analyzing Self-Supervising Learning Across Domains. It contains implementations for Supervision, ...
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Self-supervised representation learning has achieved impressive results in recent years, with experiments primarily coming on ImageNet or other similarly ...
Jul 30, 2022 · In this paper, we investigate how sensitive video self-supervised learning is to the current conventional benchmark and whether methods.
Extending and Analyzing Self-supervised Learning Across Domains. https://doi.org/10.1007/978-3-030-58574-7_43 ·. Journal: Lecture Notes in Computer Science ...
2019. Extending and analyzing self-supervised learning across domains. B Wallace, B Hariharan. Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK ...
Extending and Analyzing Self-Supervised Learning Across Domains Bram Wallace, Bharath Hariharan In ECCV, 2020. TLDR : An analysis of how well self ...
Pretraining convolutional neural networks via self-supervision, and applying them in transfer learning, is an incredibly fast-growing field that is rapidly and ...