S2-BNNS2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
Stars: ✭ 53 (-23.19%)
Mutual labels: self-supervised-learning, contrastive-learning
TCEThis repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).
Stars: ✭ 51 (-26.09%)
Mutual labels: self-supervised-learning, contrastive-learning
ViCC[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.
Stars: ✭ 33 (-52.17%)
Mutual labels: self-supervised-learning, contrastive-learning
object-aware-contrastiveObject-aware Contrastive Learning for Debiased Scene Representation (NeurIPS 2021)
Stars: ✭ 44 (-36.23%)
Mutual labels: self-supervised-learning, contrastive-learning
GCLList of Publications in Graph Contrastive Learning
Stars: ✭ 25 (-63.77%)
Mutual labels: self-supervised-learning, contrastive-learning
Revisiting-Contrastive-SSLRevisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
Stars: ✭ 81 (+17.39%)
Mutual labels: self-supervised-learning, contrastive-learning
CLMROfficial PyTorch implementation of Contrastive Learning of Musical Representations
Stars: ✭ 216 (+213.04%)
Mutual labels: self-supervised-learning, contrastive-learning
SimclrSimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
Stars: ✭ 2,720 (+3842.03%)
Mutual labels: self-supervised-learning, contrastive-learning
info-nce-pytorchPyTorch implementation of the InfoNCE loss for self-supervised learning.
Stars: ✭ 160 (+131.88%)
Mutual labels: self-supervised-learning, contrastive-learning
CLSAofficial implemntation for "Contrastive Learning with Stronger Augmentations"
Stars: ✭ 48 (-30.43%)
Mutual labels: self-supervised-learning, contrastive-learning
G-SimCLRThis is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.
Stars: ✭ 69 (+0%)
Mutual labels: self-supervised-learning, contrastive-learning
3DInfomaxMaking self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
Stars: ✭ 107 (+55.07%)
Mutual labels: self-supervised-learning, graph-representation-learning
awesome-efficient-gnnCode and resources on scalable and efficient Graph Neural Networks
Stars: ✭ 498 (+621.74%)
Mutual labels: graph-representation-learning, contrastive-learning
SCL📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).
Stars: ✭ 42 (-39.13%)
Mutual labels: self-supervised-learning, contrastive-learning
DisContCode for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors".
Stars: ✭ 13 (-81.16%)
Mutual labels: self-supervised-learning, contrastive-learning
PICParametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020
Stars: ✭ 41 (-40.58%)
Mutual labels: self-supervised-learning, contrastive-learning
Pytorch Metric LearningThe easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Stars: ✭ 3,936 (+5604.35%)
Mutual labels: self-supervised-learning, contrastive-learning
GeDMLGeneralized Deep Metric Learning.
Stars: ✭ 30 (-56.52%)
Mutual labels: self-supervised-learning, contrastive-learning
SoCo[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning
Stars: ✭ 125 (+81.16%)
Mutual labels: self-supervised-learning, contrastive-learning