This paper is aimed at 3D object understanding from 2D images, including articulated objects in active vision environment, using interactive, and internet virtual reality techniques. Generally speaking, an articulated object can be divided into two portions: main rigid portion and articulated portion. ...
Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes. These methods involve learning how to combine information from multiple view-points. However, the camera view-points from which these views are obtained ar...
3D scene from an input image (or a set of multi-view images), whereby the contents of the image(s) are causally explained in terms of models of instantiated objects, each with their own type, shape, appearance and pose, along with global variables like scene lighting and camera parameters...
- 2806 aerial images from different sensors and platforms; - Image size: 800 × 800 to about 4000 × 4000; - objects with a wide variety of scales, orientations, and shapes;- 15 common object categories;- DOTA contains 188, 282 instances; - Labeled by an arbitrary (8 dof) quadrilateral...
3d). The COF fragments in Fig. 3a,b are saturated with additional hydrogen atoms and the NICS maps resemble those of the monomers in Fig. 2. The NICS values of all fragments are added in Fig. 3c. Interestingly, this yields values very similar to the ones of a completely closed 2D COF...
Main findings include mixed levels of "quasi" geometrical understandings, misconceptions about length and angles, and ambiguous uses of geometrical language for location, direction, and movement. These have implications for future teaching and learning about 2D shapes with particular reference to VRLE....
- Boundary extraction from 2D/3D shapes - Geometric deep learning on 3D and higher dimensions - Generative methods for parametric representations - Novel shape descriptors and embeddings for geometric deep learning - Deep learning on non-Euclidean geometries ...
In this paper, we explore how the observation of different articulation states provides evidence for part structure and motion of 3D objects. Our method takes as input a pair of unsegmented shapes representing two different articulation states of two functionally related objects, and induces their ...
To address this challenge, we propose to harness pre-trained vision-language (VL) foundation models that encode extensive knowledge from image-text pairs to generate captions for multi-view images of 3D scenes. This allows us to establish explicit associations between 3D shapes and semantic-rich ...
In general, these approaches are often based on cer- tain prior assumptions of some particular property of the 3D object and hence may not generalize well. Deep learning: While deep learning has been very popu- lar in 2D images for many years, it has just been applied in 3D recently ...