[1] Supervised Contrastive Learning (NIPS 2020)
[2] Generalized Category Discovery
[3] Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
[4] Multi-Source domain adaptation via supervised contrastive learning and confident consistency regularization (BMVC 2021)
[5] Learning Transferable Visual Models From Natural Language Supervision (Contrastive Language-Image Pre-training)
[6] Semi-Supervised Learning via Compact Latent Space Clustering
[7] Contrastive Multiview coding
[8] Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
[9] Continual Contrastive Learning
<AAAI 2022>
[1] Unsupervised Representation for Semantic Segmentation by Implicit Cycle-Attention Contrastive Learning
[2] Dual Contrastive Learning for General Face Forgery Detection
[3] Improved Text Classification via Contrastive Adversarial Training
[4] Perceiving Stroke-Semantic Context: Hierarchical Contrastive Learning for Robust Scene Text Recognition
[5] Mutual Contrastive Learning for Visual Representation Learning
[6] Image Difference Captioning with Pre-Training and Contrastive Learning
[7] Boosting Contrastive Learning with Relation Knowledge Distillation
[8] Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation
[9] Semantically Contrastive Learning for Low-Light Image Enhancement
[10] Learning from Label Proportions with Prototypical Contrastive Clustering
[11] Evidential Neighborhood Contrastive Learning for Universal Domain Adaptation
[12] Boost Supervised Pretraining for Visual Transfer Learning: Implications of Self-Supervised Contrastive Representation Learning
[13] GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
[14] Frequency-Aware Contrastive Learning for Neural Machine Translation
[15] Sequence Level Contrastive Learning for Text Summarization
[16] Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives
[17] Separated Contrastive Learning for Organ-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation
[18] SAIL: Self-Augmented Graph Contrastive Learning
[19] Context-Based Contrastive Learning for Scene Text Recognition
[20] ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification
[21] AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators
[22] C2L: Causally Contrastive Learning for Robust Text Classification
[23] Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives
[24] Max-Margin Contrastive Learning
[25] CODE: Contrastive Pre-Training with Adversarial Fine-Tuning for Zero-Shot Expert Linking
<AAAI 2021>
[1] PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning
[2] Contrastive Transformation for Self-Supervised Correspondence Learning
[3] Contrastive Clustering
[4] Contrastive Adversarial Learning for Person Independent Facial Emotion Recognition
[5] Self-Supervised Pre-Training and Contrastive Representation Learning for Multiple-Choice Video QA
[6] Contrastive and Generative Graph Convolutional Networks for Graph-Based SemiSupervised Learning
[7] Learning a Few-Shot Embedding Model with Contrastive Learning
[8] Gradient Regularized Contrastive Learning for Continual Domain Adaptation
[9] Towards Effective Context for Meta-Reinforcement Learning: An Approach Based on Contrastive Learning
[10] Contrastive Self-Supervised Learning for Graph Classification
[11] A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection
[12] Learning Invariant Representations Using Inverse Contrastive Loss
[13] Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing
<NIPS 2021>
[1] Compressed Video Contrastive Learning
[2] Unsupervised Part Discovery from Contrastive Reconstruction
[3] Improving Contrastive Learning on Imbalanced Data via Open-World Sampling
[4] Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
[5] Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
[6] Task-Adaptive Neural Network Search with Meta-Contrastive
[7] A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning
[8] Teaching an Active Learner with Contrastive Examples
[9] Contrastive Laplacian Eigenmaps
[10] Object-aware Contrastive Learning for Debiased Scene Representation
[11] Disentangled Contrastive Learning on Graphs
[12] Looking Beyond Single Images for Contrastive Semantic Segmentation Learning
[13] Multi-view Contrastive Graph Clustering
[14] Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
[15] Contrastive Learning of Global and Local Video Representations
[16] Directed Graph Contrastive Learning
[17] Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels
[18] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
[19] Robust Contrastive Learning Using Negative Samples with Diminished Semantics
[20] Aligning Pretraining for Detection via Object-Level Contrastive Learning
[21] Artistic Style Transfer with Internal-external Learning and Contrastive Learning
[22] Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels
[23] Contrastively Disentangled Sequential Variational Autoencoder
[24] Local plasticity rules can learn deep representations using self-supervised contrastive predictions
[25] Provable Representation Learning for Imitation with Contrastive Fourier Features
[26] Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer
[27] Pseudo-Spherical Contrastive Divergence
[28] Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing
[29] On Contrastive Representations of Stochastic Processes
[30] Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training
[31] Contrastive Learning for Neural Topic Model
[32] Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning
[33] CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation
[34] Can contrastive learning avoid shortcut solutions?
[35] A Contrastive Learning Approach for Training Variational Autoencoder
[36] When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
[37] Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
[38] Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning
[39] Contrastive Reinforcement Learning of Symbolic Reasoning Domains
[40] Adversarial Graph Augmentation to Improve Graph Contrastive Learning
[41] COHESIV: Contrastive Object and Hand Embedding Segmentation In Video
[42] Contrastive Active Inference
[43] InfoGCL: Information-Aware Graph Contrastive Learning
[44] Time-series Generation by Contrastive Imitation
[45] Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning
[46] Inverse Problems Leveraging Pre-trained Contrastive Representations
[47] Intriguing Properties of Contrastive Losses
<NIPS 2020>
[1] Space-Time Correspondence as a Contrastive Random Walk
[2] Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
[3] Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object
[4] Hard Negative Mixing for Contrastive Learning
[5] Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
[6] Adversarial Self-Supervised Contrastive Learning
[7] Supervised Contrastive Learning
[8] Contrastive Learning with Adversarial Examples
[9] Noise-Contrastive Estimation for Multivariate Point Processes
[10] LoCo: Local Contrastive Representation Learning
[11] What Makes for Good Views for Contrastive Learning?
[12] CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
[13] Debiased Contrastive Learning
[14] High-contrast “gaudy” images improve the training of deep neural network models of visual cortex
[15] Soft Contrastive Learning for Visual Localization
[16] Robust Pre-Training by Adversarial Contrastive Learning
[17] Multi-label Contrastive Predictive Coding
[18] Graph Contrastive Learning with Augmentations
[19] Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding
[20] Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning
[21] Joint Contrastive Learning with Infinite Possibilities
[22] ContraGAN: Contrastive Learning for Conditional Image Generation
[23] Cycle-Contrast for Self-Supervised Video Representation Learning
[24] CoMIR: Contrastive Multimodal Image Representation for Registration
[25] Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
[26] Learning Global Transparent Models consistent with Local Contrastive Explanations
[27] Contrastive learning of global and local features for medical image segmentation with limited annotations
<ICLR 2022>
[1] Poisoning and Backdooring Contrastive Learning
[2] Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption
[3] Contrastive Fine-grained Class Clustering via Generative Adversarial Networks
[4] Conditional Contrastive Learning with Kernel
[5] Contrastive Learning is Just Meta-Learning
[6] Incremental False Negative Detection for Contrastive Learning
[7] Understanding Dimensional Collapse in Contrastive Self-supervised Learning
[8] Chaos is a Ladder: A New Understanding of Contrastive Learning
[9] Anomaly Detection for Tabular Data with Internal Contrastive Learning
[10] CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting
[11] Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning
[12] Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View
[13] Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning
[14] ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning
<ICLR 2021>
[1] Contrastive Divergence Learning is a Time Reversal Adversarial Game
[2] Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
[3] Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
[4] Contrastive Learning with Hard Negative Samples
[5] What Should Not Be Contrastive in Contrastive Learning
[6] Training GANs with Stronger Augmentations via Contrastive Discriminator
[7] Improving Transformation Invariance in Contrastive Representation Learning
[8] Active Contrastive Learning of Audio-Visual Video Representations
[9] Contrastive Syn-to-Real Generalization
[10] Prototypical Contrastive Learning of Unsupervised Representations
[11] Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
[12] Conditional Negative Sampling for Contrastive Learning of Visual Representations
[13] Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
<ICLR 2020>
[1] Contrastive Representation Distillation
[2] Contrastive Learning of Structured World Models
<CVPR 2021>
[1] Contrastive Learning for Compact Single Image Dehazing
[2] Contrastive Learning Based Hybrid Networks for Long-Tailed Image Classification
[3] Dual-Stream Multiple Instance Learning Network for Whole Slide Image Classification With Self-Supervised Contrastive Learning
[4] Complementary Relation Contrastive Distillation
[5] Mining Better Samples for Contrastive Learning of Temporal Correspondence
[6] CoLA: Weakly-Supervised Temporal Action Localization With Snippet Contrastive Learning
[7] Semi-Supervised Action Recognition With Temporal Contrastive Learning
[8] Interventional Video Grounding With Dual Contrastive Learning
[9] DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network
[10] Neighborhood Contrastive Learning for Novel Class Discovery
[11] Contrastive Embedding for Generalized Zero-Shot Learning
[12] CLCC: Contrastive Learning for Color Constancy
[13] Dense Contrastive Learning for Self-Supervised Visual Pre-Training
[14] COMPLETER: Incomplete Multi-View Clustering via Contrastive Prediction
<ECCV 2020>
[1] Contrastive Learning for Weakly Supervised Phrase Grounding
<ICCV 2021>
[1] A Broad Study on the Transferability of Visual Representations With Contrastive Learning
[2] Region-Aware Contrastive Learning for Semantic Segmentation
[3] Vi2CLR: Video and Image for Visual Contrastive Learning of Representation
[4] Co2L: Contrastive Continual Learning
[5] Dual Contrastive Loss and Attention for GANs
[6] Improving Contrastive Learning by Visualizing Feature Transformation
[7] Self-Supervised Visual Representations Learning by Contrastive Mask Prediction
[8] Graph Contrastive Clustering
[9] Weakly Supervised Contrastive Learning
[10]
[11] Parametric Contrastive Learning
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