Self-Supervised Learning
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Benchmarks
DABS
STL-10
CIFAR-10
CIFAR-100
TinyImageNet
cifar10
cifar100
CREMA-D
Tiny ImageNet
Most implemented
A Simple Framework for Contrastive Learning of Visual Representations
Masked Autoencoders Are Scalable Vision Learners
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Emerging Properties in Self-Supervised Vision Transformers
Bootstrap your own latent: A new approach to self-supervised Learning
Supervised Contrastive Learning
Papers
Surface-volume self-supervised representation learning of brain MRI for genetic discovery
Existing genome-wide association studies (GWAS) of brain imaging provide predefined or deep-learning-derived imaging phenotypes, yet these phenotypes come from either volumetric scans or cortical surface meshes, so each …
Self-Supervised LearningRepresentation LearningBeyond Decodability: Do Acoustic Factors Drive Predictions in Speech-Based Alzheimer's Assessment?
Speech-based Alzheimer's disease (AD) assessments increasingly rely on pretrained self-supervised learning (SSL) models that learn acoustic representations directly from raw audio, exposing the model to recording factors…
Self-Supervised LearningI Have a Stream: Making Self-Supervised Learning Work on Continuous Video
Self-supervised learning draws inspiration from infant visual development, yet standard training pipelines bear little resemblance to it: images are independently sampled and globally shuffled across epochs. We study sel…
Self-Supervised LearningEvolvingAvatar: Interactive 3D Head Generation That Adapts as Conversations Unfold
Interactive 3D head generation requires coordinated speaking and listening motion that responds to an evolving conversation. Existing generators use incoming observations as context but keep their parameters fixed, leavi…
Self-Supervised LearningTT-VidT: Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining
Comparisons in video self-supervised learning often evaluate complete training recipes rather than isolating the method itself: architecture, objective, data exposure, schedule, scale, and decoder capacity can all vary a…
Self-Supervised LearningTactile-JEPA: Topology-Aware Self-Supervised Representation Learning for Distributed Tactile Sensors
Tactile sensing is an essential modality for robots performing contact-rich, dexterous manipulation, particularly under visual occlusion. While pre-trained image encoders are standard in robot learning pipelines, tactile…
Self-Supervised LearningRepresentation Learning