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Found 5 papers, 5 papers with code
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
Leveraging nearest neighbor retrieval for self-supervised representation learning has proven beneficial with object-centric images.
CrOC: Cross-View Online Clustering for Dense Visual Representation Learning
More importantly, the clustering algorithm conjointly operates on the features of both views, thereby elegantly bypassing the issue of content not represented in both views and the ambiguous matching of objects from one crop to the other.
Ranked #11 on
Unsupervised Semantic Segmentation
on COCO-Stuff-27
Adaptive Similarity Bootstrapping for Self-Distillation based Representation Learning
Most self-supervised methods for representation learning leverage a cross-view consistency objective i. e., they maximize the representation similarity of a given image's augmented views.
Global-Local Self-Distillation for Visual Representation Learning
The downstream accuracy of self-supervised methods is tightly linked to the proxy task solved during training and the quality of the gradients extracted from it.
Motion Prediction Using Temporal Inception Module
We argue that the diverse temporal scales are important as they allow us to look at the past frames with different receptive fields, which can lead to better predictions.
