Hi @ranahanocka ,
Your work seems really impressive. I am trying to reconstruct the shape (superquadric) parameters given the point cloud. For a single shape, I have achieved satisfactory results, but I guess point2mesh with appropriate adaptations, could outperform my current results. I've posted my experiments here.
Anyway, while trying to generalize the model such that it could represent an arbitrary object as a composition of superquadrics, I got stuck.
A single superquadric is represented with 8 parameters (size along x, y, and z axis, offset along axes and two shape parameters). So first step would be to adapt point2mesh for a single superquadric regression and the next step, I guess, would be to somehow represent the input point cloud as a composition of multiple shapes.
I have read your Point2Mesh article and now I am going through your latest article. I would be very thankful if you could provide any suggestions about how to adapt your model for single and multiple shape parameters regression,
Hi @ranahanocka , Your work seems really impressive. I am trying to reconstruct the shape (superquadric) parameters given the point cloud. For a single shape, I have achieved satisfactory results, but I guess point2mesh with appropriate adaptations, could outperform my current results. I've posted my experiments here. Anyway, while trying to generalize the model such that it could represent an arbitrary object as a composition of superquadrics, I got stuck. A single superquadric is represented with 8 parameters (size along x, y, and z axis, offset along axes and two shape parameters). So first step would be to adapt point2mesh for a single superquadric regression and the next step, I guess, would be to somehow represent the input point cloud as a composition of multiple shapes. I have read your Point2Mesh article and now I am going through your latest article. I would be very thankful if you could provide any suggestions about how to adapt your model for single and multiple shape parameters regression,
Thanks!