activity
20162023
most citedTranSOP: Transformer-based Multimodal Classification for Stroke Treatment Outcome Prediction

21 citations · 45 across the 16 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.CV2022

Refining Action Boundaries for One-stage Detection

Hanyuan Wang, Majid Mirmehdi, Dima Damen +1

Current one-stage action detection methods, which simultaneously predict action boundaries and the corresponding class, do not estimate or use a measure of confidence in their boun…

eess.IV2022★ 1 cited

Video-TransUNet: Temporally Blended Vision Transformer for CT VFSS Instance Segmentation

Chengxi Zeng, Xinyu Yang, Majid Mirmehdi +2

We propose Video-TransUNet, a deep architecture for instance segmentation in medical CT videos constructed by integrating temporal feature blending into the TransUNet deep learning…

cs.CV2022★ 1 cited

Detecting Humans in RGB-D Data with CNNs

Kaiyang Zhou, Adeline Paiement, Majid Mirmehdi

We address the problem of people detection in RGB-D data where we leverage depth information to develop a region-of-interest (ROI) selection method that provides proposals to two c…

cs.CV2022

Inertial Hallucinations -- When Wearable Inertial Devices Start Seeing Things

Alessandro Masullo, Toby Perrett, Tilo Burghardt +3

We propose a novel approach to multimodal sensor fusion for Ambient Assisted Living (AAL) which takes advantage of learning using privileged information (LUPI). We address two majo…

cs.CV2022

Dynamic Curriculum Learning for Great Ape Detection in the Wild

Xinyu Yang, Tilo Burghardt, Majid Mirmehdi

We propose a novel end-to-end curriculum learning approach for sparsely labelled animal datasets leveraging large volumes of unlabelled data to improve supervised species detectors…

cs.CV2022

TVNet: Temporal Voting Network for Action Localization

Hanyuan Wang, Dima Damen, Majid Mirmehdi +1

We propose a Temporal Voting Network (TVNet) for action localization in untrimmed videos. This incorporates a novel Voting Evidence Module to locate temporal boundaries, more accur…