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Showing 76–100 of 128 papers

TitleStatusHype
From Patches to Objects: Exploiting Spatial Reasoning for Better Visual Representations—0
HMSN: Hyperbolic Self-Supervised Learning by Clustering with Ideal Prototypes—0
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of ActionsCode0
MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillationCode0
Saliency Guided Contrastive Learning on Scene Images—0
Self-Supervised and Invariant Representations for Wireless Localization—0
Promoting Semantic Connectivity: Dual Nearest Neighbors Contrastive Learning for Unsupervised Domain Generalization—0
Establishing a stronger baseline for lightweight contrastive modelsCode0
Flaky Performances when Pretraining on Relational Databases—0
Unsupervised Visual Representation Learning via Mutual Information Regularized AssignmentCode0
Depth Contrast: Self-Supervised Pretraining on 3DPM Images for Mining Material ClassificationCode0
Correlation between Alignment-Uniformity and Performance of Dense Contrastive RepresentationsCode0
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps—0
Slimmable Networks for Contrastive Self-supervised LearningCode0
On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning—0
HOME: High-Order Mixed-Moment-based Embedding for Representation Learning—0
Unsupervised Visual Representation Learning by Synchronous Momentum GroupingCode0
DSPNet: Towards Slimmable Pretrained Networks based on Discriminative Self-supervised Learning—0
Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation LearningCode0
Federated Momentum Contrastive Clustering—0
Self-Supervised Learning for Invariant Representations from Multi-Spectral and SAR Images—0
Divergence-aware Federated Self-Supervised LearningCode0
VNIbCReg: VICReg with Neighboring-Invariance and better-Covariance Evaluated on Non-stationary Seismic Signal Time SeriesCode0
Measuring Self-Supervised Representation Quality for Downstream Classification using Discriminative Features—0
Fuse Local and Global Semantics in Representation Learning—0
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