79 citations · 608 across the 98 of their papers we have counts for
14 papers · 2 filters
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…
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…
Line Graphics Digitization: A Step Towards Full Automation
Omar Moured, Jiaming Zhang, Alina Roitberg +2
The digitization of documents allows for wider accessibility and reproducibility. While automatic digitization of document layout and text content has been a long-standing focus of…
OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic Segmentation
Fei Teng, Jiaming Zhang, Kunyu Peng +3
Light field cameras are capable of capturing intricate angular and spatial details. This allows for acquiring complex light patterns and details from multiple angles, significantly…
READMem: Robust Embedding Association for a Diverse Memory in Unconstrained Video Object Segmentation
Stéphane Vujasinović, Sebastian Bullinger, Stefan Becker +3
We present READMem (Robust Embedding Association for a Diverse Memory), a modular framework for semi-automatic video object segmentation (sVOS) methods designed to handle unconstra…
Exploring Few-Shot Adaptation for Activity Recognition on Diverse Domains
Kunyu Peng, Di Wen, David Schneider +5
Domain adaptation is essential for activity recognition to ensure accurate and robust performance across diverse environments, sensor types, and data sources. Unsupervised domain a…
FishDreamer: Towards Fisheye Semantic Completion via Unified Image Outpainting and Segmentation
Hao Shi, Yu Li, Kailun Yang +7
This paper raises the new task of Fisheye Semantic Completion (FSC), where dense texture, structure, and semantics of a fisheye image are inferred even beyond the sensor field-of-v…
Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images
Zdravko Marinov, Rainer Stiefelhagen, Jens Kleesiek
Interactive segmentation reduces the annotation time of medical images and allows annotators to iteratively refine labels with corrective interactions, such as clicks. While existi…
Delivering Arbitrary-Modal Semantic Segmentation
Jiaming Zhang, Ruiping Liu, Hao Shi +6
Multimodal fusion can make semantic segmentation more robust. However, fusing an arbitrary number of modalities remains underexplored. To delve into this problem, we create the DeL…
360BEV: Panoramic Semantic Mapping for Indoor Bird's-Eye View
Zhifeng Teng, Jiaming Zhang, Kailun Yang +5
Seeing only a tiny part of the whole is not knowing the full circumstance. Bird's-eye-view (BEV) perception, a process of obtaining allocentric maps from egocentric views, is restr…
Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images based on Physiological and Anatomical Cues
Verena Jasmin Hallitschke, Tobias Schlumberger, Philipp Kataliakos +6
Recently, deep learning enabled the accurate segmentation of various diseases in medical imaging. These performances, however, typically demand large amounts of manual voxel annota…