Event cameraImage de-occlusionSpiking neural networkImage restorationRemoving dense foreground occlusion from images and reconstructing the target of interest is a critical vision task. In previous studies, it
Users can control it to reach, move and manipulate objects in their surround- ings, with the benefit of enhanced autonomy in daily- living activities. The Jaco® robot can be easily re-located and fixed on one side of the wheelchair (right or left). The con- trol system of the ...
In standard Transformer architectures, the concept of sequence order or temporal position is not inherently understood. This can be a significant drawback when dealing with time-series data prevalent in engineering systems, such as sensor readings over time or chronological event logs. To address this...
event or activity has just begun (FIG. 11B) or is nearly complete (FIG. 11C), such as by indicating how much of the display area is “filled”, e.g., by a graphic that appears to be a liquid, sand, etc. Alternatively, such animations or other graphics can adapt to the position ...
However, synthesizing images solely from event streams is ill-posed since only the brightness changes are recorded in the event stream, and the initial brightness is unknown. In this paper, we propose an event-enhanced multi-modal fusion hybrid network for image de-occlusion, which uses event ...
Traditional frame- based image de-occlusion methods may lead to fatal errors when facing extremely dense occlusions due to the lack of valid information available from the limited input occluded frames. Event cameras are bio-inspired vision sensors that record the brightness changes at each pixel ...
we propose an event-en-hanced multi-modal fusion hybrid network for image de-occlusion,which uses event streams to provide complete scene information and frames to provide color and texture information.An event stream encoder based on the spiking neural network(SNN)is proposed to en-code and ...
presents an integrated approach for accurate human motion detections by combining Adapted Canny Edge detection as a preprocessing step, backbone-modified Mask R-CNN for precise segmentation, Hybrid RDA-WOA-based RNN as a classification, and a Multiple-hypothesis model for effective occlusion handling. ...
event or activity has just begun (FIG. 11B) or is nearly complete (FIG. 11C), such as by indicating how much of the display area is “filled”, e.g., by a graphic that appears to be a liquid, sand, etc. Alternatively, such animations or other graphics can adapt to the position ...
Traditional frame- based image de-occlusion methods may lead to fatal errors when facing extremely dense occlusions due to the lack of valid information available from the limited input occluded frames. Event cameras are bio-inspired vision sensors that record the brightness changes at each pixel ...