We demonstrate that viewpoint-invariant representations can be obtained from images for a useful class of 3D smooth object. The class of surfaces are those generated as the envelope of a sphere of varying radius swept along an axis. This class includes canal surfaces and surfaces of revolution....
We demonstrate that viewpoint-invariant representations can be obtained from images for a useful class of 3D smooth object. The class of surfaces are those generated as the envelope of a sphere of varying radius swept along an axis. This class includes canal surfaces and surfaces of revolution....
We also show the efficiency of transferring the learned representations from NTU RGB+D to obtain the first ever unsupervised cross-view and cross-subject rank correlation results on the multi-view human movement quality dataset, QMAR, and marginally improve on the-state-of-the-art supervised ...
Before beginning, we need to use Instant-NGP to construct NeRF representations for the 1000 objects in IM3D, which will take approximately 24 hours. However, if you only want to conduct attacks or run simple demos, you can opt to train NeRF for a subset of the objects. Due to limited ...
Finally, the multitasking learning (MTL) method is employed to jointly train trajectory planning and high-level control tasks based on learned representations and previous motions. Results of extensive experimental evaluations on a large autonomous driving dataset with various weather/lighting conditions ...
Unsupervised Learning of View-Invariant Action Representations. In Proceedings of the Advances in Neural Information Processing Systems, Montreal, OC, Canada, 3–8 December 2018; pp. 1254–1264. [Google Scholar] Lakhal, M.I.; Lanz, O.; Cavallaro, A. View-LSTM: Novel-View Video Synthesis ...
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A second memory system sustains view-invariant representations of 3D objects. The view-dependent memory system has a storage capacity of 3-4 representations and the view-invariant memory system has a storage capacity of 1-2 representations. These systems can operate independently from one another ...
A method for learning image representations comprises receiving a pair of images, generating a set of candidate patches in each image, identifying features in each patch, arranging the patches in pairs and comparing a distance between a feature in the first image to a feature in the second ...
Our results showcase that skeleton representations learned from ViA are generic enough to improve upon state-of-the-art action classification accuracy, not only on 3D laboratory datasets such as NTU-RGB+D 60 and NTU-RGB+D 120, but also on real-world datasets where only 2D data are ...