self-supervised-or-unsupervised-representation-learning.md

CVPR-2023-Papers

Application
New collections

Self-Supervised or Unsupervised Representation Learning

Title	Repo	Paper	Video
SimpleNet: A Simple Network for Image Anomaly Detection and Localization
Masked Image Modeling with Local Multi-Scale Reconstruction
AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders			➖
ActMAD: Activation Matching to Align Distributions for Test-Time-Training
Rethinking Out-of-Distribution (OOD) Detection: Masked Image Modeling is All You Need
DLBD: A Self-Supervised Direct-Learned Binary Descriptor
Cut and Learn for Unsupervised Object Detection and Instance Segmentation
Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration
Masked Motion Encoding for Self-Supervised Video Representation Learning			➖
Stare at what You See: Masked Image Modeling without Reconstruction
Hard Patches Mining for Masked Image Modeling
Multi-Mode Online Knowledge Distillation for Self-Supervised Visual Representation Learning
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale			➖
MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis
Token Boosting for Robust Self-Supervised Visual Transformer Pre-Training	➖
Unsupervised 3D Point Cloud Representation Learning by Triangle Constrained Contrast for Autonomous Driving	➖
Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond	➖		➖
Integrally Pre-Trained Transformer Pyramid Networks
Mixed Autoencoder for Self-Supervised Visual Representation Learning	➖
Correlational Image Modeling for Self-Supervised Visual Pre-Training
Shepherding Slots to Objects: Towards Stable and Robust Object-Centric Learning
Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric			➖
Evolved Part Masking for Self-Supervised Learning			➖
Change-Aware Sampling and Contrastive Learning for Satellite Images
Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems			➖
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks
RILS: Masked Visual Reconstruction in Language Semantic Space			➖
Three Guidelines You Should know for Universally Slimmable Self-Supervised Learning
BASiS: Batch Aligned Spectral Embedding Space	➖		➖
Co-Salient Object Detection with Uncertainty-Aware Group Exchange-Masking	➖
Hyperbolic Contrastive Learning for Visual Representations beyond Objects
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm			➖
MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-based Self-Supervised Pre-Training
OmniAL: A Unified CNN Framework for Unsupervised Anomaly Localization	➖		➖
TinyMIM: An Empirical Study of Distilling MIM Pre-Trained Models			➖
ALSO: Automotive Lidar Self-Supervision by Occupancy Estimation
Non-Contrastive Unsupervised Learning of Physiological Signals from Video
CrOC: Cross-View Online Clustering for Dense Visual Representation Learning
MOVES: Manipulated Objects in Video Enable Segmentation
Self-Supervised Representation Learning for CAD	➖
Movies2Scenes: using Movie Metadata to Learn Scene Representation	➖
PointCMP: Contrastive Mask Prediction for Self-Supervised Learning on Point Cloud Videos
Texture-guided Saliency Distilling for Unsupervised Salient Object Detection			➖
Multi-Realism Image Compression with a Conditional Generator	➖		➖
Understanding Masked Autoencoders via Hierarchical Latent Variable Models
GeoMAE: Masked Geometric Target Prediction for Self-Supervised Point Cloud Pre-Training
Siamese DETR
Generalizable Implicit Neural Representations via Instance Pattern Composers			➖
Pose-Disentangled Contrastive Learning for Self-Supervised Facial Representation
OT-Filter: An Optimal Transport Filter for Learning with Noisy Labels			➖
Teacher-Generated Spatial-Attention Labels Boost Robustness and Accuracy of Contrastive Models
Spatio-Temporal Self-Supervised Learning for Point Clouds in the Wild
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
Learning Decorrelated Representations Efficiently using Fast Fourier Transform
Beyond Appearance: A Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Learning Geometry-Aware Representations by Sketching
Improving Visual Representation Learning through Perceptual Understanding			➖
MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers			➖
Unsupervised Object Localization: Observing the Background to Discover Objects
MCF: Mutual Correction Framework for Semi-Supervised Medical Image Segmentation
DivClust: Controlling Diversity in Deep Clustering
On Data Scaling in Masked Image Modeling	➖		➖
Revealing the Dark Secrets of Masked Image Modeling			➖
Open-Set Representation Learning through Combinatorial Embedding	➖		➖
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
ToThePoint: Efficient Contrastive Learning of 3D Point Clouds via Recycling			➖
MetaViewer: Towards a Unified Multi-View Representation
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
Understanding Masked Image Modeling via Learning Occlusion Invariant Feature	➖
CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning
Regularize Implicit Neural Representation by Itself			➖