Scientists have developed a new method called Human3R that can quickly reconstruct 3D scenes and people from videos taken with just one camera. This approach is important because it allows for faster and more efficient processing of video data, which could lead to breakthroughs in applications such as virtual reality, surveillance, and robotics.
Read Full Paper →Scientists created a new dataset of videos recorded at night to test how well computers can understand what's happening in low-light conditions. This dataset, called EgoNight, should help researchers develop better computer vision models that can work as well in the dark as they do in daylight, which is important for real-world applications like robots and self-driving cars.
Read Paper →Scientists created a new system called DropD-SLAM that uses artificial intelligence to help a camera map its surroundings in 3D without needing special depth sensors. This system is important because it could make it easier and less expensive for robots and self-driving cars to navigate spaces using only cameras, which is a major step forward for the field of navigation technology.
Read Paper →We developed a new way for computers to generate images that can take into account things like camera settings and blur effects, allowing users to have more control over what they see. This could be useful for photographers or anyone who wants to be able to easily adjust the focus or blur in an image without affecting the rest of it.
Read Paper →Scientists used computer models to create more realistic virtual driving environments, which can help improve self-driving cars' ability to navigate new situations. By using these virtual environments, the team found a way to make self-driving cars learn from simulated experiences.
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