Abstract: Hand gesture recognition (HGR) is one of the most challenging tasks because it is very sensitive to occlusion or background.

ABSTRACT. Hand gesture recognition (HGR) is one of the most challeng- ing tasks because it is very sensitive to occlusion or back- ground.

A new multi-modal fusion network that quantifies and converges the mutual influence of two modalities and proposes the self-labeling-based adaptive guidance ...

This paper analyzes the synergistic effect of the two complementary modalities, and then proposes a new multi-modal fusion network that quantifies and ...

We propose a methods for the recognition of hand gestures using Gabor wavelets (GW), Radon transform (RT) and texture features for gesture ... [Show full ...

Dive into the research topics of 'RPFNET: COMPLEMENTARY FEATURE FUSION FOR HAND GESTURE RECOGNITION'. Together they form a unique fingerprint. Sort by; Weight ...

Oct 19, 2022 · 1: RPFNET: COMPLEMENTARY FEATURE FUSION FOR HAND GESTURE RECOGNITION · 2: BUILDING INSPECTION TOOLKIT: UNIFIED EVALUATION AND STRONG BASELINES ...

MIFD-Net : a hand gesture recognition model based on feature fusion of MLP and CNN ... RPFNET: Complementary Feature Fusion for Hand Gesture Recognition. October ...

Our model uses a panoramic segmentation network to separate object instances and backgrounds in scenes, and uses the attention mechanism to learn the semantic ...

Face recognition under ideal conditions is now considered a well-solved problem with advances in deep learning. Recognizing faces under occlusion, however, ...