On Partial Prototype Collapse in the DINO Family of Self-Supervised Methods

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Govindarajan, Hariprasath, Sidén, Per, Roll, Jacob, Lindsten, Fredrik
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DINO as a von Mises-Fisher mixture model
by: Govindarajan, Hariprasath, et al.
Published: (2024)

QUEST: A robust attention formulation using query-modulated spherical attention
by: Govindarajan, Hariprasath, et al.
Published: (2026)

Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning
by: Arteaga, Gabriel Y., et al.
Published: (2025)

S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving
by: Wozniak, Maciej K., et al.
Published: (2024)

Understanding Ice Crystal Habit Diversity with Self-Supervised Learning
by: Ko, Joseph, et al.
Published: (2025)

Data or Language Supervision: What Makes CLIP Better than DINO?
by: Liu, Yiming, et al.
Published: (2025)

XAI for Skin Cancer Detection with Prototypes and Non-Expert Supervision
by: Correia, Miguel, et al.
Published: (2024)

Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods
by: Otero, Daniel, et al.
Published: (2024)

Task Prototype-Based Knowledge Retrieval for Multi-Task Learning from Partially Annotated Data
by: Oh, Youngmin, et al.
Published: (2026)

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning
by: Wu, Yizhou, et al.
Published: (2026)

Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition
by: Feng, Hao, et al.
Published: (2024)

DINO-MX: A Modular & Flexible Framework for Self-Supervised Learning
by: Gokmen, Mahmut Selman, et al.
Published: (2025)

Self-Supervised Learning of Color Constancy
by: Ernst, Markus R., et al.
Published: (2024)

Blockwise Self-Supervised Learning at Scale
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2023)

When Multi-Task Learning Meets Partial Supervision: A Computer Vision Review
by: Fontana, Maxime, et al.
Published: (2023)

On Pretraining Data Diversity for Self-Supervised Learning
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2024)

Rethinking The Uniformity Metric in Self-Supervised Learning
by: Fang, Xianghong, et al.
Published: (2024)

Self-Supervised Quantization-Aware Knowledge Distillation
by: Zhao, Kaiqi, et al.
Published: (2024)

Matrix Information Theory for Self-Supervised Learning
by: Zhang, Yifan, et al.
Published: (2023)

StruMPL: Multi-task Dense Regression under Disjoint Partial Supervision and MNAR Labels
by: Asiyabi, Reza M., et al.
Published: (2026)

AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics
by: Su, Stella, et al.
Published: (2025)

HASSOD: Hierarchical Adaptive Self-Supervised Object Detection
by: Cao, Shengcao, et al.
Published: (2024)

Self-Supervised Learning for Identifying Defects in Sewer Footage
by: Otero, Daniel, et al.
Published: (2024)

LDReg: Local Dimensionality Regularized Self-Supervised Learning
by: Huang, Hanxun, et al.
Published: (2024)

Self-Supervised Multi-Frame Neural Scene Flow
by: Liu, Dongrui, et al.
Published: (2024)

True Self-Supervised Novel View Synthesis is Transferable
by: Mitchel, Thomas W., et al.
Published: (2025)

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations
by: Eastwood, Cian, et al.
Published: (2023)

SENSE: Self-Supervised Neural Embeddings for Spatial Ensembles
by: Gadirov, Hamid, et al.
Published: (2025)

Multitask Multimodal Self-Supervised Learning for Medical Images
by: Simionescu, Cristian
Published: (2025)

Prototype Guided Backdoor Defense
by: Amula, Venkat Adithya, et al.
Published: (2025)

A Survey of the Self Supervised Learning Mechanisms for Vision Transformers
by: Khan, Asifullah, et al.
Published: (2024)

An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders
by: Lowe, Scott C., et al.
Published: (2024)

Dataset Distillation for Pre-Trained Self-Supervised Vision Models
by: Cazenavette, George, et al.
Published: (2025)

Patronus: Interpretable Diffusion Models with Prototypes
by: Weng, Nina, et al.
Published: (2025)

FILS: Self-Supervised Video Feature Prediction In Semantic Language Space
by: Ahmadian, Mona, et al.
Published: (2024)

CNN Explainability with Multivector Tucker Saliency Maps for Self-Supervised Models
by: Bouayed, Aymene Mohammed, et al.
Published: (2024)

Bridging Diversity and Uncertainty in Active learning with Self-Supervised Pre-Training
by: Doucet, Paul, et al.
Published: (2024)

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
by: Balestriero, Randall, et al.
Published: (2025)

From Semantic To Instance: A Semi-Self-Supervised Learning Approach
by: Najafian, Keyhan, et al.
Published: (2025)

SatDINO: A Deep Dive into Self-Supervised Pretraining for Remote Sensing
by: Straka, Jakub, et al.
Published: (2025)