most citedDelivering Arbitrary-Modal Semantic Segmentation

5 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

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…

cs.CV20241 cited

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…

cs.CV2024

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…

cs.CV20231 cited

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…

cs.CV20235 cited

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…