Results 11 to 20 of about 1,166,366 (314)
Learning Dense Correspondence from Synthetic Environments
2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2022 Estimation of human shape and pose from a single image is a challenging task. It is an even more difficult problem to map the identified human shape onto a 3D human model. Existing methods map manually labelled human pixels in real 2D images onto the 3D surface, which is prone to human error, and the sparsity of available annotated data often leads to ...
Lal, Mithun +5 more
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Extended reality in digital learning: influence, opportunities and risks’ mitigation
Освітній вимір, 2021 The paper discusses AR/VR/MR/XR technologies in learning namely their influence/ opportunity and risks’ mitigation. Main aspects are as follows: methodology (factors influencing a student’s cybersickness in AR/VR/MR/XR, the improved model of the ...
Oleksandr Burov, Olga Pinchuk
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MultiEarth 2023 - Multimodal Learning for Earth and Environment Workshop and Challenge [PDF]
arXiv.org, 2023 The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) is the second annual CVPR workshop aimed at the monitoring and analysis of the health of Earth ecosystems by leveraging the vast amount of remote sensing data that is ...
Miriam Cha +12 more
semanticscholar +1 more source
WebArena: A Realistic Web Environment for Building Autonomous Agents [PDF]
International Conference on Learning Representations, 2023 With advances in generative AI, there is now potential for autonomous agents to manage daily tasks via natural language commands. However, current agents are primarily created and tested in simplified synthetic environments, leading to a disconnect with ...
Shuyan Zhou +10 more
semanticscholar +1 more source
Education and Information Technologies : Official Journal of the IFIP technical committee on Education, 2022 Modern text-to-speech voices can convey social cues ideal for narrating multimedia learning materials. Amazon Alexa has a unique feature among modern text-to-speech vocalizers as she can infuse enthusiasm cues into her synthetic voice.
Tze Wei Liew +4 more
semanticscholar +1 more source
Denoising-Based Decoupling-Contrastive Learning for Ubiquitous Synthetic Face Images
IEEE Access, 2023 With the improvement of generative models such as GPT-4, GANs, and diffusion models, synthetic face images are increasingly pervading the current digital environment.
Yupeng Zhu, Xinyi Shen, Peilun Du
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Education Sciences, 2021 This document evidences an innovative methodological vision in the teaching-learning process of the English language focused on the inclusion of all its students in a heterogeneous learning environment. Learning a foreign language as a second language is
Jorge Cárdenas, Esteban Inga
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Galaxy mergers in Subaru HSC-SSP: A deep representation learning approach for identification, and the role of environment on merger incidence [PDF]
Astronomy & Astrophysics, 2023 We take a deep learning-based approach for galaxy merger identification in Subaru HSC-SSP, specifically through the use of deep representation learning and fine-tuning, with the aim of creating a pure and complete merger sample within the HSC-SSP survey.
K. Omori +9 more
semanticscholar +1 more source
Applied Sciences, 2022 This paper aims at analyzing the performance of reinforcement learning (RL) agents when trained in environments created by a generative adversarial network (GAN).
Smita Mahajan +7 more
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Boosting Deep Reinforcement Learning Agents with Generative Data Augmentation
Applied Sciences, 2023 Data augmentation is a promising technique in improving exploration and convergence speed in deep reinforcement learning methodologies. In this work, we propose a data augmentation framework based on generative models for creating completely novel states
Tasos Papagiannis +2 more
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