Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
cs.CV, cs.LG
Submitted: 2026-05-28
Updated: 2026-05-28
Comments: ICML 2026
License: http://creativecommons.org/licenses/by/4.0/
The gist: We propose Intrinsic Quality (IQ), a validation-free metric designed to estimate the inherent potential of face recognition (FR) datasets to produce high-performance models without the need for
Terminology
Abstract
We propose Intrinsic Quality (IQ), a validation-free metric designed to estimate the inherent potential of face recognition (FR) datasets to produce high-performance models without the need for full-scale training. IQ integrates two components: (i) a Neighbor-Consistency Score that quantifies local identity label agreement via nearest neighbors, and (ii) Global Representation Subspace Complexity (Effective Rank, ER), which captures the underlying embedding geometry and dataset diversity. IQ allows for rapid evaluation using lightweight proxy models or data subsets, facilitating dataset diagnosis and curation prior to resource-intensive full-scale training. We describe an experimental protocol tailored to clean, noisy, and mixed-quality FR datasets, and outline evaluation methodologies to validate IQ's predictive power for downstream performance.
Sources
- X-Factor: Quality Is a Dataset-Intrinsic Property
- Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods
- An Embedding is Worth a Thousand Noisy Labels
- Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
- Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
- Deep Residual Learning for Image Recognition
- Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
- Matrix Information Theory for Self-Supervised Learning
- PaCo-FR: Patch-Pixel Aligned End-to-End Codebook Learning for Facial Representation Pre-training
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models