activity
20242026
most citedSecond FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data

17 citations · 34 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Physics-Bounded mmWave Sensing for Schedulable, Privacy-Preserving Human Pose Estimation

Shuntian Zheng, Hongyang He, Jiaqi Li +6

Millimeter-wave (mmWave) is a promising modality for human pose estimation (HPE) in mobile deployments with strong privacy requirements and limited resources, such as fall detectio…

cs.HC2026

Doppler Prompting for Stable mmWave-based Human Pose Estimation

Shuntian Zheng, Jiaqi Li, Xiaoman Lu +2

Millimeter-wave (mmWave) enables privacy-preserving, illumination-robust human pose estimation (HPE), with each mmWave frame represented as a range-angle-Doppler tensor, providing…

cs.CV2025

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment

Shuhao Han, Haotian Fan, Fangyuan Kong +112

This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…

cs.CV2024★ 17 cited

Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data

Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56

Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…

cs.CV2024★ 17 cited

Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data

Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55

Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…