Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

no code implementations • 11 Apr 2024 • Yanhao Wu, Tong Zhang, Wei Ke, Congpei Qiu, Sabine Susstrunk, Mathieu Salzmann

Subsequently, we introduce a context-aware feature learning strategy, which encodes object patterns without relying on their specific context by aggregating object features across various scenes.

Object Scene Understanding +1

De-coupling and De-positioning Dense Self-supervised Learning

no code implementations • 29 Mar 2023 • Congpei Qiu, Tong Zhang, Wei Ke, Mathieu Salzmann, Sabine Süsstrunk

Dense Self-Supervised Learning (SSL) methods address the limitations of using image-level feature representations when handling images with multiple objects.

Data Augmentation Object +5

Leverage Your Local and Global Representations: A New Self-Supervised Learning Strategy

no code implementations • CVPR 2022 • Tong Zhang, Congpei Qiu, Wei Ke, Sabine Süsstrunk, Mathieu Salzmann

In essence, this strategy ignores the fact that two crops may truly contain different image information, e. g., background and small objects, and thus tends to restrain the diversity of the learned representations.

Self-Supervised Learning Transfer Learning