3 papers
cs.AI2025
MLLMs are Deeply Affected by Modality Bias
Xu Zheng, Chenfei Liao, Yuqian Fu +15
Recent advances in Multimodal Large Language Models (MLLMs) have shown promising results in integrating diverse modalities such as texts and images. MLLMs are heavily influenced by…
cs.CV2025
OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation
Ding Zhong, Xu Zheng, Chenfei Liao +5
Segment Anything Model 2 (SAM2) has emerged as a strong base model in various pinhole imaging segmentation tasks. However, when applying it to domain, the significant f…
cs.CV2024
Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation
Xu Zheng, Haiwei Xue, Jialei Chen +6
Simultaneously using multimodal inputs from multiple sensors to train segmentors is intuitively advantageous but practically challenging. A key challenge is unimodal bias, where mu…