69 citations · 409 across the 84 of their papers we have counts for
101 papers
CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity
Hao Shi, Chengshan Pang, Jiaming Zhang +6
Roadside camera-driven 3D object detection is a crucial task in intelligent transportation systems, which extends the perception range beyond the limitations of vision-centric vehi…
Elevating Skeleton-Based Action Recognition with Efficient Multi-Modality Self-Supervision
Yiping Wei, Kunyu Peng, Alina Roitberg +6
Self-supervised representation learning for human action recognition has developed rapidly in recent years. Most of the existing works are based on skeleton data while using a mult…
Towards Privacy-Supporting Fall Detection via Deep Unsupervised RGB2Depth Adaptation
Hejun Xiao, Kunyu Peng, Xiangsheng Huang +4
Fall detection is a vital task in health monitoring, as it allows the system to trigger an alert and therefore enabling faster interventions when a person experiences a fall. Altho…
On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars
Walter Morales-Alvarez, Novel Certad, Alina Roitberg +2
For driver observation frameworks, clean datasets collected in controlled simulated environments often serve as the initial training ground. Yet, when deployed under real driving c…
Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines
Alexander Jaus, Constantin Seibold, Kelsey Hermann +5
In this study, we present a method for generating automated anatomy segmentation datasets using a sequential process that involves nnU-Net-based pseudo-labeling and anatomy-guided…
Open Scene Understanding: Grounded Situation Recognition Meets Segment Anything for Helping People with Visual Impairments
Ruiping Liu, Jiaming Zhang, Kunyu Peng +5
Grounded Situation Recognition (GSR) is capable of recognizing and interpreting visual scenes in a contextually intuitive way, yielding salient activities (verbs) and the involved…