Special Report, News, Americas

[AprpdlNuh]

First, gravity is a force that causes objects to attract one another. The simplest way to understand gravity is through Isaac Newton's law of universal gravitation. This law states that every particle in the universe attracts every other particle. The more massive an object is, the more strongly it attracts other objects. The closer objects are, the more strongly they attract each other. An enormous object, like the Earth, easily attracts objects that are close to it, like apples hanging from trees. Scientists haven't decided exactly what causes this attraction, but they believe it exists everywhere in the universe. Second, air is a fluid that behaves essentially the same way liquids do. Like liquids, air is made of microscopic particles that move in relation to one another. Air also moves like water does -- in fact, some aerodynamic tests take place underwater instead of in the air. The particles in gasses, like the ones that make up air, are simply farther apart and move faster than the particles in liquids.|We propose Locformer, a Transformer-based model for video grounding which operates at a constant memory footprint regardless of the video length, i.e. number of frames. Locformer is designed for tasks where it is necessary to process the entire long video and at its core lie two main contributions. First, our model incorporates a new sampling technique that splits the input feature sequence into a fixed number of sections and selects a single feature per section using a stochastic approach, which allows us to obtain a feature sample-set that is representative of the video content for the task at hand while keeping the memory footprint constant. Second, we propose a modular design that separates functionality, enabling us to learn an inductive bias via supervising the self-attention heads, while also effectively leveraging pre-trained text and video encoders. We test our proposals on relevant benchmark datasets for video grounding, showing that not only Locformer can achieve excellent results including state-of-the-art performance on YouCookII, but also that our sampling technique is more effective than competing counterparts and that it consistently improves the performance of prior work, by up to 3.13% in the mean temporal IoU, ultimately leading to a new state-of-the-art performance on Charades-STA.




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