Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Damirchi, Hamed"'
Autor:
Rodriguez-Opazo, Cristian, Abbasnejad, Ehsan, Teney, Damien, Marrese-Taylor, Edison, Damirchi, Hamed, Hengel, Anton van den
Contrastive Language-Image Pretraining (CLIP) stands out as a prominent method for image representation learning. Various architectures, from vision transformers (ViTs) to convolutional networks (ResNets) have been trained with CLIP to serve as gener
Externí odkaz:
http://arxiv.org/abs/2405.17139
Autor:
Rodriguez-Opazo, Cristian, Marrese-Taylor, Edison, Abbasnejad, Ehsan, Damirchi, Hamed, Jara, Ignacio M., Bravo-Marquez, Felipe, Hengel, Anton van den
Contrastive Language-Image Pretraining (CLIP) stands out as a prominent method for image representation learning. Various neural architectures, spanning Transformer-based models like Vision Transformers (ViTs) to Convolutional Networks (ConvNets) lik
Externí odkaz:
http://arxiv.org/abs/2312.14400
Monolithic neural networks that make use of a single set of weights to learn useful representations for downstream tasks explicitly dismiss the compositional nature of data generation processes. This characteristic exists in data where every instance
Externí odkaz:
http://arxiv.org/abs/2306.01316
Publikováno v:
Computer Vision and Image Understanding Volume 233, August 2023, 103722
Due to the compact and rich high-level representations offered, skeleton-based human action recognition has recently become a highly active research topic. Previous studies have demonstrated that investigating joint relationships in spatial and tempo
Externí odkaz:
http://arxiv.org/abs/2301.13090
The incremental poses computed through odometry can be integrated over time to calculate the pose of a device with respect to an initial location. The resulting global pose may be used to formulate a second, consistency based, loss term in a deep odo
Externí odkaz:
http://arxiv.org/abs/2107.00366
Inertial Measurement Units (IMUs) are interceptive modalities that provide ego-motion measurements independent of the environmental factors. They are widely adopted in various autonomous systems. Motivated by the limitations in processing the noisy m
Externí odkaz:
http://arxiv.org/abs/2101.07061
Visual odometry networks commonly use pretrained optical flow networks in order to derive the ego-motion between consecutive frames. The features extracted by these networks represent the motion of all the pixels between frames. However, due to the e
Externí odkaz:
http://arxiv.org/abs/2011.08634
Human Activity Recognition (HAR) is a challenging problem that needs advanced solutions than using handcrafted features to achieve a desirable performance. Deep learning has been proposed as a solution to obtain more accurate HAR systems being robust
Externí odkaz:
http://arxiv.org/abs/2007.03063