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August 26, 2025With a novel parallel-computing architecture, a CAD-to-USD pipeline, and the use of OpenUSD as ground truth, a new simulator can explore hundreds of sensor configurations in the time it takes to test just a few physical setups.
Featured news
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International Workshop on Acoustic Signal Enhancement (IWAENC) 20242024We propose a practical framework to synthesize the broadband sound-field on a small rigid surface based on the physics of sound propagation. The sound-field is generated as a composite map of two components: the room component and the device component, with acoustic plane waves as the core tool for the generation. This decoupling of room and device components significantly reduces the problem complexity
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2024Self-supervised learning methods have demonstrated impressive performance across visual understanding tasks, including human behavior understanding. However, there has been limited work for self-supervised learning for egocentric social videos. Visual processing in such contexts faces several challenges, including noisy input, limited availability of egocentric social data, and the absence of pretrained
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International Workshop on Acoustic Signal Enhancement (IWAENC) 20242024We describe a new method for estimating the direction of sound in a reverberant environment from basic principles of sound propagation. The method utilizes SNR-adaptive features from time-delay and energy of the directional components after acoustic wave decomposition of the observed sound field to estimate the line-of-sight direction under noisy and reverberant conditions. The effectiveness of the approach
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2024In this work, we propose an efficient Video-Language Alignment (ViLA) network. Our ViLA model addresses both efficient frame sampling and effective cross-modal alignment in a unified way. In our ViLA network, we design a new learnable text-guided Frame-Prompter together with a cross-modal distillation (QFormer-Distiller) module. Pretrained large image-language models have shown promising results on problems
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Sixth Symposium on Advances in Approximate Bayesian Inference2024With the advances of computational power, there has been a rapid development in complex systems to predict certain outputs for industrial problems. Attributing outputs to input features, or output changes to input or system changes has been a critical and challenging problem in many real world applications. In industrial settings, a system could be a chain of large scale models or simulators, or a combination
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