5 citations · 13 across the 47 of their papers we have counts for
9 papers · 1 filter
ObjectFinder: An Open-Vocabulary Assistive System for Interactive Object Search by Blind People
Ruiping Liu, Jiaming Zhang, Angela Schön +6
Searching for objects in unfamiliar scenarios is a challenging task for blind people. It involves specifying the target object, detecting it, and then gathering detailed informatio…
OneBEV: Using One Panoramic Image for Bird's-Eye-View Semantic Mapping
Jiale Wei, Junwei Zheng, Ruiping Liu +3
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 w…
@Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology
Xin Jiang, Junwei Zheng, Ruiping Liu +4
As Vision-Language Models (VLMs) advance, human-centered Assistive Technologies (ATs) for helping People with Visual Impairments (PVIs) are evolving into generalists, capable of pe…
Comb, Prune, Distill: Towards Unified Pruning for Vision Model Compression
Jonas Schmitt, Ruiping Liu, Junwei Zheng +2
Lightweight and effective models are essential for devices with limited resources, such as intelligent vehicles. Structured pruning offers a promising approach to model compression…
Open Panoramic Segmentation
Junwei Zheng, Ruiping Liu, Yufan Chen +5
Panoramic images, capturing a 360° field of view (FoV), encompass omnidirectional spatial information crucial for scene understanding. However, it is not only costly to obtain trai…
Referring Atomic Video Action Recognition
Kunyu Peng, Jia Fu, Kailun Yang +8
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…
RoDLA: Benchmarking the Robustness of Document Layout Analysis Models
Yufan Chen, Jiaming Zhang, Kunyu Peng +4
Before developing a Document Layout Analysis (DLA) model in real-world applications, conducting comprehensive robustness testing is essential. However, the robustness of DLA models…
Skeleton-Based Human Action Recognition with Noisy Labels
Yi Xu, Kunyu Peng, Di Wen +7
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. Howe…
Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation
Ruiping Liu, Jiaming Zhang, Kunyu Peng +6
Integrating information from multiple modalities enhances the robustness of scene perception systems in autonomous vehicles, providing a more comprehensive and reliable sensory fra…