Multi-modal Classification
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Benchmarks
Most implemented
What Makes Training Multi-Modal Classification Networks Hard?
Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
Hateful Meme Detection through Context-Sensitive Prompting and Fine-Grained Labeling
PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
Contrastive Audio-Visual Masked Autoencoder
Papers
Multi-Modal Building Inspection via Perceiver IO Fusion of Satellite and Street-Level Imagery
We present a multi-modal classification framework that fuses satellite and street-level imagery through a Perceiver IO architecture operating on spatial patch tokens from a shared DINOv2 backbone. The design naturally ha…
Multi-modal ClassificationA Hybrid CNN and ML Framework for Multi-modal Classification of Movement Disorders Using MRI and Brain Structural Features
Atypical Parkinsonian Disorders (APD), also known as Parkinson-plus syndrome, are a group of neurodegenerative diseases that include progressive supranuclear palsy (PSP) and multiple system atrophy (MSA). In the early st…
Multi-modal ClassificationToken Entropy Regularization for Multi-modal Antenna Affiliation Identification
Accurate antenna affiliation identification is crucial for optimizing and maintaining communication networks. Current practice, however, relies on the cumbersome and error-prone process of manual tower inspections. We pr…
Multi-modal ClassificationD-CAT: Decoupled Cross-Attention Transfer between Sensor Modalities for Unimodal Inference
Cross-modal transfer learning is used to improve multi-modal classification models (e.g., for human activity recognition in human-robot collaboration). However, existing methods require paired sensor data at both trainin…
Human Activity RecognitionMulti-modal ClassificationTransfer LearningSurformer v2: A Multimodal Classifier for Surface Understanding from Touch and Vision
Multimodal surface material classification plays a critical role in advancing tactile perception for robotic manipulation and interaction. In this paper, we present Surformer v2, an enhanced multi-modal classification ar…
Multi-modal ClassificationBi-cephalic self-attended model to classify Parkinson's disease patients with freezing of gait
Parkinson's Disease (PD) often results in motor and cognitive impairments, including gait dysfunction, particularly in patients with freezing of gait (FOG). Current detection methods are either subjective or reliant on s…
Multi-modal Classification