3 papers
cs.CV2023
Gait Data Augmentation using Physics-Based Biomechanical Simulation
Mritula Chandrasekaran, Jarek Francik, Dimitrios Makris
This paper focuses on addressing the problem of data scarcity for gait analysis. Standard augmentation methods may produce gait sequences that are not consistent with the biomechan…
cs.CV2023
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…
cs.CV2023
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…