activity
20172026
most citedFirst Order Motion Model for Image Animation

145 citations · 224 across the 24 of their papers we have counts for

collaborators
Showing 2023Show all

8 papers · 1 filter

cs.CV2023

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…

cs.LG2023

Weighted Ensemble Models Are Strong Continual Learners

Imad Eddine Marouf, Subhankar Roy, Enzo Tartaglione +1

In this work, we study the problem of continual learning (CL) where the goal is to learn a model on a sequence of tasks, such that the data from the previous tasks becomes unavaila…

cs.CV2023

Mini but Mighty: Finetuning ViTs with Mini Adapters

Imad Eddine Marouf, Enzo Tartaglione, Stéphane Lathuilière

Vision Transformers (ViTs) have become one of the dominant architectures in computer vision, and pre-trained ViT models are commonly adapted to new tasks via fine-tuning. Recent wo…

cs.CV2023

Enhancing Plasticity for First Session Adaptation Continual Learning

Imad Eddine Marouf, Subhankar Roy, Stéphane Lathuilière +1

The integration of large pre-trained models (PTMs) into Class-Incremental Learning (CIL) has facilitated the development of computationally efficient strategies such as First-Sessi…

cs.CV2023★ 2 cited

The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation

Giacomo Zara, Alessandro Conti, Subhankar Roy +3

Source-Free Video Unsupervised Domain Adaptation (SFVUDA) task consists in adapting an action recognition model, trained on a labelled source dataset, to an unlabelled target datas…

cs.CV2023

Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic Segmentation

Tianyu Li, Subhankar Roy, Huayi Zhou +2

To overcome the domain gap between synthetic and real-world datasets, unsupervised domain adaptation methods have been proposed for semantic segmentation. Majority of the previous…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 11 cited

Promptable Game Models: Text-Guided Game Simulation via Masked Diffusion Models

Willi Menapace, Aliaksandr Siarohin, Stéphane Lathuilière +4

Neural video game simulators emerged as powerful tools to generate and edit videos. Their idea is to represent games as the evolution of an environment's state driven by the action…