Snehashis Majhi

24 papers A* 1A 3B 2Journal 11Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
B-MoE: A Body-Part-Aware Mixture-of-Experts "All Parts Matter" Approach to Micro-Action Recognition.
CoRR
Nishit Poddar, Aglind Reka, Diana Laura Borza, Snehashis Majhi, Michal Balazia, Abhijit Das, François Brémond
2025 J jnl
From SAM to DINOv2: Towards Distilling Foundation Models to Lightweight Baselines for Generalized Polyp Segmentation.
CoRR
Shivanshu Agnihotri, Snehashis Majhi, Deepak Ranjan Nayak, Debesh Jha
2025 A conf
Guess Future Anomalies from Normalcy: Forecasting Abnormal Behavior in Real-World Videos.
WACV
Snehashis Majhi, Mohammed Guermal, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond
2025 A* conf
Just Dance with pi! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection.
CVPR
Snehashis Majhi, Giacomo D'Amicantonio, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, Egor Bondarev, François Brémond
2025 J jnl
Just Dance with π! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection.
CoRR
Snehashis Majhi, Giacomo D'Amicantonio, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, Egor Bondarev, François Brémond
2025 — conf
Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation.
MICCAI (11)
Tapas Kumar Dutta, Snehashis Majhi, Deepak Ranjan Nayak, Debesh Jha
2025 J jnl
Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation.
CoRR
Tapas Kumar Dutta, Snehashis Majhi, Deepak Ranjan Nayak, Debesh Jha
2025 J jnl
Mixture of Experts Guided by Gaussian Splatters Matters: A new Approach to Weakly-Supervised Video Anomaly Detection.
CoRR
Giacomo D'Amicantonio, Snehashis Majhi, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond, Egor Bondarev
2025 A conf
SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation.
WACV
Tapas Kumar Dutta, Snehashis Majhi, Deepak Ranjan Nayak, Debesh Jha
2024 J jnl
Human-Scene Network: A novel baseline with self-rectifying loss for weakly supervised video anomaly detection.
Comput. Vis. Image Underst.
Snehashis Majhi, Rui Dai, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond
2024 A conf
OE-CTST: Outlier-Embedded Cross Temporal Scale Transformer for Weakly-supervised Video Anomaly Detection.
WACV
Snehashis Majhi, Rui Dai, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond
2024 J jnl
SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation.
CoRR
Tapas Kumar Dutta, Snehashis Majhi, Deepak Ranjan Nayak, Debesh Jha
2024 — conf
What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon.
ECCV Workshops (7)
Utkarsh Tiwari, Snehashis Majhi, Michal Balazia, François Brémond
2024 J jnl
What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon.
CoRR
Utkarsh Tiwari, Snehashis Majhi, Michal Balazia, François Brémond
2023 J jnl
Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection.
CoRR
Snehashis Majhi, Rui Dai, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond
2023 — conf
TrichANet: An Attentive Network for Trichogramma Classification.
VISIGRAPP (4: VISAPP)
Agniv Chatterjee, Snehashis Majhi, Vincent Calcagno, François Brémond
2022 — conf
Multi-level 3DCNN with Min-Max Ranking Loss for Weakly-Supervised Video Anomaly Detection.
ICONIP (7)
Snehashis Majhi, Deepak Ranjan Nayak, Ratnakar Dash, Pankaj Kumar Sa
2021 B conf
DAM: Dissimilarity Attention Module for Weakly-supervised Video Anomaly Detection.
AVSS
Snehashis Majhi, Srijan Das, François Brémond
2021 — conf
Feature Modulating Two-Stream Deep Convolutional Neural Network for Glaucoma Detection in Fundus Images.
CVIP (2)
Snehashis Majhi, Deepak Ranjan Nayak
2021 B conf
Weakly-supervised Joint Anomaly Detection and Classification.
FG
Snehashis Majhi, Srijan Das, François Brémond, Ratnakar Dash, Pankaj Kumar Sa
2021 J jnl
Weakly-supervised Joint Anomaly Detection and Classification.
CoRR
Snehashis Majhi, Srijan Das, François Brémond, Ratnakar Dash, Pankaj Kumar Sa
2020 J jnl
Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images.
Multim. Tools Appl.
Deepak Ranjan Nayak, Dibyasundar Das, Ratnakar Dash, Snehashis Majhi, Banshidhar Majhi
2020 — conf
Temporal Pooling in Inflated 3DCNN for Weakly-supervised Video Anomaly Detection.
ICCCNT
Snehashis Majhi, Ratnakar Dash, Pankaj Kumar Sa
2019 — conf
Two-Stream CNN Architecture for Anomalous Event Detection in Real World Scenarios.
CVIP (2)
Snehashis Majhi, Ratnakar Dash, Pankaj Kumar Sa