A GRU Neural Network with attention mechanism for detection of risk situations on multimodal lifelog data. - Rupayan Mallick; Thinhinane Yebda; Jenny Benois-Pineau; Akka Zemmari; Marion Pech; Hélène Amieva (CBMI, 2021)

Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos. - Di Yang 002; Rui Dai 001; Yaohui Wang 001; Rupayan Mallick; Luca Minciullo; Gianpiero Francesca; François Brémond (WACV, 2021)

I Saw: A Self-Attention Weighted Method for Explanation of Visual Transformers. - Rupayan Mallick; Jenny Benois-Pineau; Akka Zemmari (ICIP, 2022)

Pooling Transformer for Detection of Risk Events in In-The-Wild Video Ego Data. - Rupayan Mallick; Jenny Benois-Pineau; Akka Zemmari; Thinhinane Yebda; Marion Pech; Hélène Amieva; Laura Middleton (ICPR, 2022)

A Hybrid Transformer Network for Detection of Risk Situations on Multimodal Life-Log Health Data. - Rupayan Mallick; Jenny Benois-Pineau; Akka Zemmari; Marion Pech; Thinhinane Yebda; Hélène Amieva; Laura Middleton (ICDAR@ICMR, 2022)

Detection of Risky Situations for Frail Adults With Hybrid Neural Networks on Multimodal Health Data. - Rupayan Mallick; Thinhinane Yebda; Jenny Benois-Pineau; Akka Zemmari; Marion Pech; Hélène Amieva (IEEE Multim., 2022)

Lasagna: Layered Score Distillation for Disentangled Object Relighting. - Dina Bashkirova; Arijit Ray; Rupayan Mallick; Sarah Adel Bargal; Jianming Zhang 001; Ranjay Krishna; Kate Saenko (CoRR, 2023)

Explainable Deep Learning for the Application to Multimodal Data. (Apprentissage Profond explicable Application sur les données multimodales). - Rupayan Mallick (2023)

IFI: Interpreting for Improving: A Multimodal Transformer with an Interpretability Technique for Recognition of Risk Events. - Rupayan Mallick; Jenny Benois-Pineau; Akka Zemmari (MMM (4), 2024)

FaithFill: Faithful Inpainting for Object Completion Using a Single Reference Image. - Rupayan Mallick; Amr Abdalla; Sarah Adel Bargal (CoRR, 2024)

A hybrid transformer with domain adaptation using interpretability techniques for the application to the detection of risk situations. - Rupayan Mallick; Jenny Benois-Pineau; Akka Zemmari; Kamel Guerda; Boris Mansencal; Hélène Amieva; Laura Middleton (Multim. Tools Appl., 2024)

D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition. - Rupayan Mallick; Sibo Dong; Nataniel Ruiz; Sarah Adel Bargal (CVPR Workshops, 2025)

GenEAva: Generating Cartoon Avatars with Fine-Grained Facial Expressions from Realistic Diffusion-based Faces. - Hao Yu 014; Rupayan Mallick; Margrit Betke; Sarah Adel Bargal (CoRR, 2025)

ViSTA: Visual Storytelling using Multi-modal Adapters for Text-to-Image Diffusion Models. - Sibo Dong; Ismail Shaheen; Maggie Shen; Rupayan Mallick; Sarah Adel Bargal (CoRR, 2025)

GIFT: Gradient-aware Immunization of diffusion models against malicious Fine-Tuning with safe concepts retention. - Amro Abdalla; Ismail Shaheen; Dan DeGenaro; Rupayan Mallick; Bogdan Raita; Sarah Adel Bargal (CoRR, 2025)

Gen-AFFECT: Generation of Avatar Fine-grained Facial Expressions with Consistent identiTy. - Hao Yu 014; Rupayan Mallick; Margrit Betke; Sarah Adel Bargal (CoRR, 2025)