1 citations · 1 across the 3 of their papers we have counts for
4 papers
Make me an Expert: Distilling from Generalist Black-Box Models into Specialized Models for Semantic Segmentation
Yasser Benigmim, Subhankar Roy, Khalid Oublal +4
The rise of Artificial Intelligence as a Service (AIaaS) democratizes access to pre-trained models via Application Programming Interfaces (APIs), but also raises a fundamental ques…
FLOSS: Free Lunch in Open-vocabulary Semantic Segmentation
Yasser Benigmim, Mohammad Fahes, Tuan-Hung Vu +2
In this paper, we challenge the conventional practice in Open-Vocabulary Semantic Segmentation (OVSS) of using averaged class-wise text embeddings, which are typically obtained by…
Collaborating Foundation Models for Domain Generalized Semantic Segmentation
Yasser Benigmim, Subhankar Roy, Slim Essid +2
Domain Generalized Semantic Segmentation (DGSS) deals with training a model on a labeled source domain with the aim of generalizing to unseen domains during inference. Existing DGS…
One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models
Yasser Benigmim, Subhankar Roy, Slim Essid +2
Adapting a segmentation model from a labeled source domain to a target domain, where a single unlabeled datum is available, is one the most challenging problems in domain adaptatio…