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Found 4 papers, 0 papers with code
Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Driving
LiDAR and camera are two critical sensors for multi-modal 3D semantic segmentation and are supposed to be fused efficiently and robustly to promise safety in various real-world scenarios.
ESA-ReID: Entropy-Based Semantic Feature Alignment for Person re-ID
Person re-identification (re-ID) is a challenging task in real-world.
VIDEO AFFECTIVE IMPACT PREDICTION WITH MULTIMODAL FUSION AND LONG-SHORT TEMPORAL CONTEXT
Feature extraction, multi-modal fusion and temporal context fusion are crucial stages for predicting valence and arousal values in the emotional impact, but have not been successfully exploited.
Video Affective Effects Prediction with Multi-modal Fusion and Shot-Long Temporal Context
We select the most suitable modalities for valence and arousal tasks respectively and each modal feature is extracted using the modality-specific pre-trained deep model on large generic dataset.
