1 citations · 1 across the 5 of their papers we have counts for
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Different Defects, Different Effects: A Controlled Audit of Face Recognition Training Data
Ana Dias, João Ribeiro Pinto, Hugo Proença +1
The development of face recognition has been strongly supported by the availability of large-scale training datasets. Among them, MS-Celeb-1M has played an important role by provid…
Robust Face Super-Resolution and Recognition Through Multi-Feature Aggregation in Diffusion Models
Marcelo dos Santos, Rayson Laroca, João Carlos Raposo Neves +1
Images acquired in surveillance environments often suffer from conditions such as low resolution, variations in pose, irregular illumination, and occlusions. Due to the low quality…
The Good, the Better, and the Best: Improving the Discriminability of Face Embeddings through Attribute-aware Learning
Ana Dias, João Ribeiro Pinto, Hugo Proença +1
Despite recent advances in face recognition, robust performance remains challenging under large variations in age, pose, and occlusion. A common strategy to address these issues is…
SRL-MAD: Structured Residual Latents for One-Class Morphing Attack Detection
Diogo J. Paulo, Hugo Proença, João C. Neves
Face morphing attacks represent a significant threat to biometric systems as they allow multiple identities to be combined into a single face. While supervised morphing attack dete…
A Multilevel Strategy to Improve People Tracking in a Real-World Scenario
Cristiano B. de Oliveira, Joao C. Neves, Rafael O. Ribeiro +1
The Palácio do Planalto, office of the President of Brazil, was invaded by protesters on January 8, 2023. Surveillance videos taken from inside the building were subsequently relea…
Embedding Aggregation for Forensic Facial Comparison
Rafael Oliveira Ribeiro, João C. R. Neves, Arnout C. C. Ruifrok +1
In forensic facial comparison, questioned-source images are usually captured in uncontrolled environments, with non-uniform lighting, and from non-cooperative subjects. The poor qu…