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Found 6 papers, 4 papers with code
Unsupervised Part Discovery via Dual Representation Alignment
Object parts serve as crucial intermediate representations in various downstream tasks, but part-level representation learning still has not received as much attention as other vision tasks.
Cross Contrasting Feature Perturbation for Domain Generalization
Domain generalization (DG) aims to learn a robust model from source domains that generalize well on unseen target domains.
Strip-MLP: Efficient Token Interaction for Vision MLP
Finally, based on the Strip MLP layer, we propose a novel \textbf{L}ocal \textbf{S}trip \textbf{M}ixing \textbf{M}odule (LSMM) to boost the token interaction power in the local region.
Rethinking Alignment and Uniformity in Unsupervised Image Semantic Segmentation
Experimental results on multiple semantic segmentation benchmarks show that our unsupervised segmentation framework specializes in catching semantic representations, which outperforms all the unpretrained and even several pretrained methods.
Ranked #1 on
Unsupervised Semantic Segmentation
on COCO-Stuff-3
Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning
The SLPT generates the representation of each single landmark from a local patch and aggregates them by an adaptive inherent relation based on the attention mechanism.
Ranked #2 on
Face Alignment
on COFW-68
Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma
EMReDL showed to effectively segment the infiltrated tumor from the partially labelled region of potential infiltration.
