2 papers
cs.CV2024
Bottleneck-based Encoder-decoder ARchitecture (BEAR) for Learning Unbiased Consumer-to-Consumer Image Representations
Pablo Rivas, Gisela Bichler, Tomas Cerny +2
Unbiased representation learning is still an object of study under specific applications and contexts. Novel architectures are usually crafted to resolve particular problems using…
cs.LG2024
On the Challenges of Creating Datasets for Analyzing Commercial Sex Advertisements to Assess Human Trafficking Risk and Organized Activity
Pablo Rivas, Tomas Cerny, Alejandro Rodriguez Perez +4
Our study addresses the challenges of building datasets to understand the risks associated with organized activities and human trafficking through commercial sex advertisements. Th…