Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Gur, Shir"'
Inverse kinematic (IK) methods recover the parameters of the joints, given the desired position of selected elements in the kinematic chain. While the problem is well-defined and low-dimensional, it has to be solved rapidly, accounting for multiple p
Externí odkaz:
http://arxiv.org/abs/2205.10837
The current methods for learning representations with auto-encoders almost exclusively employ vectors as the latent representations. In this work, we propose to employ a tensor product structure for this purpose. This way, the obtained representation
Externí odkaz:
http://arxiv.org/abs/2202.06201
Internal learning for single-image generation is a framework, where a generator is trained to produce novel images based on a single image. Since these models are trained on a single image, they are limited in their scale and application. To overcome
Externí odkaz:
http://arxiv.org/abs/2110.02900
Recent advances in using retrieval components over external knowledge sources have shown impressive results for a variety of downstream tasks in natural language processing. Here, we explore the use of unstructured external knowledge sources of image
Externí odkaz:
http://arxiv.org/abs/2104.08108
Transformers are increasingly dominating multi-modal reasoning tasks, such as visual question answering, achieving state-of-the-art results thanks to their ability to contextualize information using the self-attention and co-attention mechanisms. The
Externí odkaz:
http://arxiv.org/abs/2103.15679
Self-attention techniques, and specifically Transformers, are dominating the field of text processing and are becoming increasingly popular in computer vision classification tasks. In order to visualize the parts of the image that led to a certain cl
Externí odkaz:
http://arxiv.org/abs/2012.09838
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization
Neural network visualization techniques mark image locations by their relevancy to the network's classification. Existing methods are effective in highlighting the regions that affect the resulting classification the most. However, as we show, these
Externí odkaz:
http://arxiv.org/abs/2012.02166
We consider the task of generating diverse and novel videos from a single video sample. Recently, new hierarchical patch-GAN based approaches were proposed for generating diverse images, given only a single sample at training time. Moving to videos,
Externí odkaz:
http://arxiv.org/abs/2006.12226
Recently developed methods for rapid continuous volumetric two-photon microscopy facilitate the observation of neuronal activity in hundreds of individual neurons and changes in blood flow in adjacent blood vessels across a large volume of living bra
Externí odkaz:
http://arxiv.org/abs/2001.05076
Autor:
Gur, Shir, Wolf, Lior
Estimating depth from a single RGB images is a fundamental task in computer vision, which is most directly solved using supervised deep learning. In the field of unsupervised learning of depth from a single RGB image, depth is not given explicitly. E
Externí odkaz:
http://arxiv.org/abs/2001.05036