Two-Stream CNN Architecture for Anomalous Event Detection in Real World Scenarios. - Snehashis Majhi; Ratnakar Dash; Pankaj Kumar Sa (CVIP (2), 2019)

Temporal Pooling in Inflated 3DCNN for Weakly-supervised Video Anomaly Detection. - Snehashis Majhi; Ratnakar Dash; Pankaj Kumar Sa (ICCCNT, 2020)

Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images. - Deepak Ranjan Nayak; Dibyasundar Das; Ratnakar Dash; Snehashis Majhi; Banshidhar Majhi (Multim. Tools Appl., 2020)

DAM: Dissimilarity Attention Module for Weakly-supervised Video Anomaly Detection. - Snehashis Majhi; Srijan Das; François Brémond (AVSS, 2021)

Feature Modulating Two-Stream Deep Convolutional Neural Network for Glaucoma Detection in Fundus Images. - Snehashis Majhi; Deepak Ranjan Nayak (CVIP (2), 2021)

Weakly-supervised Joint Anomaly Detection and Classification. - Snehashis Majhi; Srijan Das; François Brémond; Ratnakar Dash; Pankaj Kumar Sa (FG, 2021)

Multi-level 3DCNN with Min-Max Ranking Loss for Weakly-Supervised Video Anomaly Detection. - Snehashis Majhi; Deepak Ranjan Nayak; Ratnakar Dash; Pankaj Kumar Sa (ICONIP (7), 2022)

TrichANet: An Attentive Network for Trichogramma Classification. - Agniv Chatterjee; Snehashis Majhi; Vincent Calcagno; François Brémond (VISIGRAPP (4: VISAPP), 2023)

What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon. - Utkarsh Tiwari; Snehashis Majhi; Michal Balazia; François Brémond (ECCV Workshops (7), 2024)

OE-CTST: Outlier-Embedded Cross Temporal Scale Transformer for Weakly-supervised Video Anomaly Detection. - Snehashis Majhi; Rui Dai 001; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; François Brémond (WACV, 2024)

Human-Scene Network: A novel baseline with self-rectifying loss for weakly supervised video anomaly detection. - Snehashis Majhi; Rui Dai 001; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; François Brémond (Comput. Vis. Image Underst., 2024)

Just Dance with pi! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection. - Snehashis Majhi; Giacomo D'Amicantonio; Antitza Dantcheva; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; Egor Bondarev; François Brémond (CVPR, 2025)

SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation. - Tapas Kumar Dutta; Snehashis Majhi; Deepak Ranjan Nayak; Debesh Jha (WACV, 2025)

Guess Future Anomalies from Normalcy: Forecasting Abnormal Behavior in Real-World Videos. - Snehashis Majhi; Mohammed Guermal; Antitza Dantcheva; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; François Brémond (WACV, 2025)

Just Dance with π! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection. - Snehashis Majhi; Giacomo D'Amicantonio; Antitza Dantcheva; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; Egor Bondarev; François Brémond (CoRR, 2025)

Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation. - Tapas Kumar Dutta; Snehashis Majhi; Deepak Ranjan Nayak; Debesh Jha (CoRR, 2025)

Mixture of Experts Guided by Gaussian Splatters Matters: A new Approach to Weakly-Supervised Video Anomaly Detection. - Giacomo D'Amicantonio; Snehashis Majhi; Quan Kong; Lorenzo Garattoni; Gianpiero Francesca; François Brémond; Egor Bondarev (CoRR, 2025)