In this paper we discuss the evaluation criteria for superquadric models recovered from the range data. We present arguments to support our belief that both quantitative and qualitative measures are required in order to evaluate a superquadric fit. The concept of superquadric contraction and dilation is introduced and used to derive a novel interpretation of the modified superquadric inside-outside function in terms of contraction/expansion factor. The same concept also gives a close initial guess for the numerical procedure computing the minimum Euclidean distance of a point from a superquadric model. The minimum Euclidean distance map is introduced as a qualitative criterion for interpretation of fit. View-dependent qualitative measures l...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...
International audienceWe present in this paper a new curve and surface implicit model. This implicit...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...
In this paper we discuss the evaluation criteria for superquadric models recovered from the range da...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
... In this paper, we present a novel approach, which is called extended superquadric, to extend su...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
Superquadrics are well known and often used 3D surface objects in computer graphics. They are used f...
Superquadrics are well known and often used 3D surface objects in computer graphics. They are used f...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
Nonparametric methods of calculating points on the curve produce the recently introduced superquadri...
Superellipses are parametric models that can be used for represent-ing two dimensional object parts ...
We present a novel approach to reliable and efficient recovery of part-descriptions in terms of supe...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...
International audienceWe present in this paper a new curve and surface implicit model. This implicit...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...
In this paper we discuss the evaluation criteria for superquadric models recovered from the range da...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
... In this paper, we present a novel approach, which is called extended superquadric, to extend su...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
Superquadrics are well known and often used 3D surface objects in computer graphics. They are used f...
Superquadrics are well known and often used 3D surface objects in computer graphics. They are used f...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
Nonparametric methods of calculating points on the curve produce the recently introduced superquadri...
Superellipses are parametric models that can be used for represent-ing two dimensional object parts ...
We present a novel approach to reliable and efficient recovery of part-descriptions in terms of supe...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...
International audienceWe present in this paper a new curve and surface implicit model. This implicit...
One natural way to measure model adequacy is by using statistical distances as loss functions. A rel...