3 citations · 9 across the 17 of their papers we have counts for
19 papers
MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection
Xu Zheng, Yuanhuiyi Lyu, Lutao Jiang +3
In this paper, we address the challenging modality-agnostic semantic segmentation (MaSS), aiming at centering the value of every modality at every feature granularity. Training wit…
EventDance++: Language-guided Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition
Xu Zheng, Lin Wang
In this paper, we address the challenging problem of cross-modal (image-to-events) adaptation for event-based recognition without accessing any labeled source image data. This task…
Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentation
Xu Zheng, Yuanhuiyi Lyu, Jiazhou Zhou +1
Fusing an arbitrary number of modalities is vital for achieving robust multi-modal fusion of semantic segmentation yet remains less explored to date. Recent endeavors regard RGB mo…
GoodSAM++: Bridging Domain and Capacity Gaps via Segment Anything Model for Panoramic Semantic Segmentation
Weiming Zhang, Yexin Liu, Xu Zheng +1
This paper presents GoodSAM++, a novel framework utilizing the powerful zero-shot instance segmentation capability of SAM (i.e., teacher) to learn a compact panoramic semantic segm…
Learning Modality-agnostic Representation for Semantic Segmentation from Any Modalities
Xu Zheng, Yuanhuiyi Lyu, Lin Wang
Image modality is not perfect as it often fails in certain conditions, e.g., night and fast motion. This significantly limits the robustness and versatility of existing multi-modal…
EIT-1M: One Million EEG-Image-Text Pairs for Human Visual-textual Recognition and More
Xu Zheng, Ling Wang, Kanghao Chen +3
Recently, electroencephalography (EEG) signals have been actively incorporated to decode brain activity to visual or textual stimuli and achieve object recognition in multi-modal A…