1 citations · 6 across the 44 of their papers we have counts for
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Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization
Kunyu Peng, Di Wen, M. Saquib Sarfraz +7
Open-Set Domain Generalization (OSDG) is a challenging task requiring models to accurately predict familiar categories while minimizing confidence for unknown categories to effecti…
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
Kunyu Peng, Di Wen, Kailun Yang +6
In Open-Set Domain Generalization (OSDG), the model is exposed to both new variations of data appearance (domains) and open-set conditions, where both known and novel categories ar…
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…