COMPASS: Fusion-Matched Supervision for Missing-Modality Human Sensing

arXiv:2604.02056 · cs.CV · Submitted 2026-04-02 · Read on arXiv

cs.CV

Submitted: 2026-04-02

Updated: 2026-09-24

Terminology

• Alignment — 9× in this paper · explained in 1 episode
• Multimodal Fusion — 9× in this paper · explained in 3 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Transformer — 8× in this paper · explained in 2 episodes
• Distillation — 7× in this paper · explained in 2 episodes
• Latent Space — 7× in this paper · explained in 7 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Regularization — 6× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Multimodal Learning — 5× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Modality Gap — 3× in this paper · explained in 4 episodes
• Point Clouds — 3× in this paper · explained in 2 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Active Inference — 2× in this paper · explained in 1 episode
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Self-Supervised Learning — 2× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes

Sources

• Distilling the Knowledge in a Neural Network
• Learning Factorized Multimodal Representations
• Deep Multimodal Learning with Missing Modality: A Survey
• Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion

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