# Unconstrained Face Detection and Open-Set Face Recognition Challenge

arXiv: https://arxiv.org/abs/1708.02337 · HTML: https://mlsanity.com/paper/1708.02337/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2017.

## Built on by (most cited first, 18 of 18)

- [Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset](https://mlsanity.com/paper/2211.01917/) (2022)
- [Student Network Learning via Evolutionary Knowledge Distillation](https://mlsanity.com/paper/2103.13811/) (2021)
- [A Survey on Open Set Recognition](https://mlsanity.com/paper/2109.00893/) (2021)
- [Ethical Considerations for Responsible Data Curation](https://mlsanity.com/paper/2302.03629/) (2023)
- [Open-Set Biometrics: Beyond Good Closed-Set Models](https://mlsanity.com/paper/2407.16133/) (2024)
- [Eight Years of Face Recognition Research: Reproducibility, Achievements and Open Issues](https://mlsanity.com/paper/2208.04040/) (2022)
- [Open-Set Face Recognition with Maximal Entropy and Objectosphere Loss](https://mlsanity.com/paper/2311.00400/) (2023)
- [LocalScore: Local Density-Aware Similarity Scoring for Biometrics](https://mlsanity.com/paper/2602.01012/) (2026)
- [Open-set Face Recognition using Ensembles trained on Clustered Data](https://mlsanity.com/paper/2308.07445/) (2023)
- [Low-Resolution Object Recognition with Cross-Resolution Relational Contrastive Distillation](https://mlsanity.com/paper/2409.02555/) (2024)
- [Watchlist Challenge: 3rd Open-set Face Detection and Identification](https://mlsanity.com/paper/2409.07220/) (2024)
- [A Comparative Analysis of the Face Recognition Methods in Video Surveillance Scenarios](https://mlsanity.com/paper/2211.02952/) (2022)
- [DaliID: Distortion-Adaptive Learned Invariance for Identification Models](https://mlsanity.com/paper/2302.05753/) (2023)
- [Open-Set Object Recognition Using Mechanical Properties During Interaction](https://mlsanity.com/paper/2311.01540/) (2023)
- [Low-Resolution Face Recognition via Adaptable Instance-Relation Distillation](https://mlsanity.com/paper/2409.02049/) (2024)
- [Distilling Generative-Discriminative Representations for Very Low-Resolution Face Recognition](https://mlsanity.com/paper/2409.06371/) (2024)
- [GaitFace: A Multimodal Dataset for Long-Range Person Identification](https://mlsanity.com/paper/2607.23542/) (2026)
- [Weight and Height Estimation from a Single Human Image Captured in the Wild](https://mlsanity.com/paper/2607.26104/) (2026)

## Abstract (arXiv)

Face detection and recognition benchmarks have shifted toward more difficult environments. The challenge presented in this paper addresses the next step in the direction of automatic detection and identification of people from outdoor surveillance cameras. While face detection has shown remarkable success in images collected from the web, surveillance cameras include more diverse occlusions, poses, weather conditions and image blur. Although face verification or closed-set face identification have surpassed human capabilities on some datasets, open-set identification is much more complex as it needs to reject both unknown identities and false accepts from the face detector. We show that unconstrained face detection can approach high detection rates albeit with moderate false accept rates. By contrast, open-set face recognition is currently weak and requires much more attention.