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pro vyhledávání: '"Liu, Ruiping"'
Autor:
Jiang, Xin, Zheng, Junwei, Liu, Ruiping, Li, Jiahang, Zhang, Jiaming, Matthiesen, Sven, Stiefelhagen, Rainer
As Vision-Language Models (VLMs) advance, human-centered Assistive Technologies (ATs) for helping People with Visual Impairments (PVIs) are evolving into generalists, capable of performing multiple tasks simultaneously. However, benchmarking VLMs for
Externí odkaz:
http://arxiv.org/abs/2409.14215
In the field of autonomous driving, Bird's-Eye-View (BEV) perception has attracted increasing attention in the community since it provides more comprehensive information compared with pinhole front-view images and panoramas. Traditional BEV methods,
Externí odkaz:
http://arxiv.org/abs/2409.13912
Lightweight and effective models are essential for devices with limited resources, such as intelligent vehicles. Structured pruning offers a promising approach to model compression and efficiency enhancement. However, existing methods often tie pruni
Externí odkaz:
http://arxiv.org/abs/2408.03046
Autor:
Zheng, Junwei, Liu, Ruiping, Chen, Yufan, Peng, Kunyu, Wu, Chengzhi, Yang, Kailun, Zhang, Jiaming, Stiefelhagen, Rainer
Panoramic images, capturing a 360{\deg} field of view (FoV), encompass omnidirectional spatial information crucial for scene understanding. However, it is not only costly to obtain training-sufficient dense-annotated panoramas but also application-re
Externí odkaz:
http://arxiv.org/abs/2407.02685
Autor:
Peng, Kunyu, Fu, Jia, Yang, Kailun, Wen, Di, Chen, Yufan, Liu, Ruiping, Zheng, Junwei, Zhang, Jiaming, Sarfraz, M. Saquib, Stiefelhagen, Rainer, Roitberg, Alina
We introduce a new task called Referring Atomic Video Action Recognition (RAVAR), aimed at identifying atomic actions of a particular person based on a textual description and the video data of this person. This task differs from traditional action r
Externí odkaz:
http://arxiv.org/abs/2407.01872
Autor:
Chen, Yufan, Zhang, Jiaming, Peng, Kunyu, Zheng, Junwei, Liu, Ruiping, Torr, Philip, Stiefelhagen, Rainer
Before developing a Document Layout Analysis (DLA) model in real-world applications, conducting comprehensive robustness testing is essential. However, the robustness of DLA models remains underexplored in the literature. To address this, we are the
Externí odkaz:
http://arxiv.org/abs/2403.14442
Autor:
Xu, Yi, Peng, Kunyu, Wen, Di, Liu, Ruiping, Zheng, Junwei, Chen, Yufan, Zhang, Jiaming, Roitberg, Alina, Yang, Kailun, Stiefelhagen, Rainer
Understanding human actions from body poses is critical for assistive robots sharing space with humans in order to make informed and safe decisions about the next interaction. However, precise temporal localization and annotation of activity sequence
Externí odkaz:
http://arxiv.org/abs/2403.09975
Autor:
Liu, Ruiping, Zhang, Jiaming, Peng, Kunyu, Chen, Yufan, Cao, Ke, Zheng, Junwei, Sarfraz, M. Saquib, Yang, Kailun, Stiefelhagen, Rainer
Integrating information from multiple modalities enhances the robustness of scene perception systems in autonomous vehicles, providing a more comprehensive and reliable sensory framework. However, the modality incompleteness in multi-modal segmentati
Externí odkaz:
http://arxiv.org/abs/2401.16923
Autor:
Peng, Kunyu, Yin, Cheng, Zheng, Junwei, Liu, Ruiping, Schneider, David, Zhang, Jiaming, Yang, Kailun, Sarfraz, M. Saquib, Stiefelhagen, Rainer, Roitberg, Alina
In real-world scenarios, human actions often fall outside the distribution of training data, making it crucial for models to recognize known actions and reject unknown ones. However, using pure skeleton data in such open-set conditions poses challeng
Externí odkaz:
http://arxiv.org/abs/2312.06330
Autor:
Chen, Yifei, Peng, Kunyu, Roitberg, Alina, Schneider, David, Zhang, Jiaming, Zheng, Junwei, Liu, Ruiping, Chen, Yufan, Yang, Kailun, Stiefelhagen, Rainer
To integrate self-supervised skeleton-based action recognition methods into autonomous robotic systems, it is crucial to consider adverse situations involving target occlusions. Such a scenario, despite its practical relevance, is rarely addressed in
Externí odkaz:
http://arxiv.org/abs/2309.12029