6 citations · 8 across the 6 of their papers we have counts for
6 papers
Spatio-Temporal State Space Model For Efficient Event-Based Optical Flow
Muhammad Ahmed Humais, Xiaoqian Huang, Hussain Sajwani +2
Event cameras unlock new frontiers that were previously unthinkable with standard frame-based cameras. One notable example is low-latency motion estimation (optical flow), which is…
EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras
Youssef Farah, Federico Paredes-Vallés, Guido De Croon +3
Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to bright…
Asynchronous Bioplausible Neuron for SNN for Event Vision
Sanket Kachole, Hussain Sajwani, Fariborz Baghaei Naeini +2
Spiking Neural Networks (SNNs) offer a biologically inspired approach to computer vision that can lead to more efficient processing of visual data with reduced energy consumption.…
Asynchronous Events-based Panoptic Segmentation using Graph Mixer Neural Network
Sanket Kachole, Yusra Alkendi, Fariborz Baghaei Naeini +2
In the context of robotic grasping, object segmentation encounters several difficulties when faced with dynamic conditions such as real-time operation, occlusion, low lighting, mot…
Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Grasping
Sanket Kachole, Xiaoqian Huang, Fariborz Baghaei Naeini +3
Object segmentation for robotic grasping under dynamic conditions often faces challenges such as occlusion, low light conditions, motion blur and object size variance. To address t…
A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment
Xiaoqian Huang, Kachole Sanket, Abdulla Ayyad +3
Taking advantage of an event-based camera, the issues of motion blur, low dynamic range and low time sampling of standard cameras can all be addressed. However, there is a lack of…