EgoEV-HandPose uses stereo event cameras and a bird's-eye-view fusion module to achieve 30.54 mm MPJPE and 86.87% gesture accuracy on a new large-scale egocentric dataset, outperforming prior RGB and event methods especially in low light and occlusion.
Event-based vision: A survey
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
A receding-horizon MLE recovers Neural-ODE parameters and event thresholds from event camera data by modeling events as a history-dependent marked point process.
SAST applies sharpness-aware minimization to surrogate-gradient SNN training and reports large gains in hard-spike accuracy on N-MNIST and DVS Gesture, including under INT8/INT4 quantization.
citing papers explorer
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EgoEV-HandPose: Egocentric 3D Hand Pose Estimation and Gesture Recognition with Stereo Event Cameras
EgoEV-HandPose uses stereo event cameras and a bird's-eye-view fusion module to achieve 30.54 mm MPJPE and 86.87% gesture accuracy on a new large-scale egocentric dataset, outperforming prior RGB and event methods especially in low light and occlusion.
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Receding-Horizon Maximum-Likelihood Estimation of Neural-ODE Dynamics and Thresholds from Event Cameras
A receding-horizon MLE recovers Neural-ODE parameters and event thresholds from event camera data by modeling events as a history-dependent marked point process.
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Sharpness-Aware Surrogate Training for On-Sensor Spiking Neural Networks
SAST applies sharpness-aware minimization to surrogate-gradient SNN training and reports large gains in hard-spike accuracy on N-MNIST and DVS Gesture, including under INT8/INT4 quantization.