Snehashis Majhi

According to our database, Snehashis Majhi authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

OE-CTST: Outlier-Embedded Cross Temporal Scale Transformer for Weakly-supervised Video Anomaly Detection.

Snehashis Majhi, Rui Dai, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection.

Snehashis Majhi, Rui Dai, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, François Brémond

CoRR, 2023

TrichANet: An Attentive Network for Trichogramma Classification.

Agniv Chatterjee, Snehashis Majhi, Vincent Calcagno, François Brémond

Proceedings of the 18th International Joint Conference on Computer Vision, 2023

2022

Multi-level 3DCNN with Min-Max Ranking Loss for Weakly-Supervised Video Anomaly Detection.

Snehashis Majhi, Deepak Ranjan Nayak, Ratnakar Dash, Pankaj Kumar Sa

Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021

Weakly-supervised Joint Anomaly Detection and Classification.

Snehashis Majhi, Srijan Das, François Brémond, Ratnakar Dash, Pankaj Kumar Sa

Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

Feature Modulating Two-Stream Deep Convolutional Neural Network for Glaucoma Detection in Fundus Images.

Snehashis Majhi, Deepak Ranjan Nayak

Proceedings of the Computer Vision and Image Processing - 6th International Conference, 2021

DAM: Dissimilarity Attention Module for Weakly-supervised Video Anomaly Detection.

Snehashis Majhi, Srijan Das, François Brémond

Proceedings of the 17th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2021

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

Temporal Pooling in Inflated 3DCNN for Weakly-supervised Video Anomaly Detection.

Snehashis Majhi, Ratnakar Dash, Pankaj Kumar Sa

Proceedings of the 11th International Conference on Computing, 2020

2019

Two-Stream CNN Architecture for Anomalous Event Detection in Real World Scenarios.

Snehashis Majhi, Ratnakar Dash, Pankaj Kumar Sa

Proceedings of the Computer Vision and Image Processing - 4th International Conference, 2019