DynIBaR, an innovative AI technique introduced by Google and Cornell researchers at CVPR 2023, generates realistic free-viewpoint renderings from a single video captured with a phone camera. It offers various video effects such as bullet time effects, video stabilization, depth of field adjustments, and slow-motion capabilities. The technique is scalable to long and complex dynamic scenes, addressing challenges faced by other methodologies. The researchers used an MLP neural network to encode dynamic scenes and directly utilized pixel data from surrounding frames to construct new views, enhancing rendering quality.
Researchers from Google and Cornell have developed a new AI technique called DynIBaR, which can generate realistic renderings of dynamic scenes from a single video captured with a smartphone camera. This technique is useful for creating visual effects such as bullet time effects, video stabilization, depth of field adjustments, and slow motion.
DynIBaR is capable of handling long videos with complex object motions and uncontrolled camera trajectories. To achieve this, the researchers modeled motion trajectory fields using learned basis functions, and introduced a temporal photometric loss to ensure temporal coherence in reconstructing dynamic scenes. They also incorporated a novel motion segmentation technique to separate static and dynamic components of the scene, improving rendering quality.
The main innovation of DynIBaR is that it doesn’t rely on a large multilayer perceptron (MLP) neural network to store all the scene details. Instead, it directly uses pixel data from surrounding frames in the video to generate new views. The foundation of the technique is based on IBRNet, an image-based rendering method used for static scenes.
This research contribution was presented at the CVPR 2023 conference in the field of computer vision. More details about the research can be found in the academic paper and on the Google Blog.
(Source: MarkTechPost)
I’m sorry, but I don’t see any action items in the meeting notes you provided. It seems to be a summary of an article about AI research. If there are specific tasks or action items that were discussed during the meeting, please provide them and I’ll be happy to help assign them to specific individuals.
