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Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation
Missing modalities at test time can cause significant degradation in the performance of multimodal systems. In this paper, we presented a simple and parameter-efficient adaptation method for …
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MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection
In real-world applications, input modalities might be missing due to factors like sensor malfunctions or data constraints. Our recent paper addresses this challenge with a method called …
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MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
Leveraging information across diverse modalities is known to enhance performance on multimodal segmentation tasks. However, effectively fusing information from different modalities remains …
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