Adobe, Inc.

Xuaner Zhang

Zhe Lin

Elya Shechtman

Kalyan Krishna Sunkavalli

Zhaowen Wang

Sohrab Amirghodsi

Connelly Barnes

Joon-Young Lee

Yuqian Zhou

Zijun Wei

Florian Kainz

Mang Tik Chiu

Embodiments are disclosed for performing wire segmentation of images using machine learning. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input image, generating, by a first trained neural network model, a global probability map representation of the input image indicating a probability value of each pixel including a representation of wires, and identifying regions of the input image indicated as including the representation of wires. The disclosed systems and methods further comprise, for each region from the identified regions, concatenating the region and information from the global probability map to create a concatenated input, and generating, by a second trained neural network model, a local probability map representation of the region based on the concatenated input, indicating pixels of the region including representations of wires. The disclosed systems and methods further comprise aggregating local probability maps for each region.

Wire segmentation for images using machine learning

Photometric stabilization for time-compressed video is described. Initially, video content captured by a video capturing device is time-compressed by selecting a subset of frames from the video content according to a frame sampling technique. Photometric characteristics are then stabilized across the frames of the time-compressed video. This involves determining correspondences of pixels in adjacent frames of the time-compressed video. Photometric transformations are then determined that describe how photometric characteristics (e.g., one or both of luminance and chrominance) change between the adjacent frames, given movement of objects through the captured scene. Based on the determined photometric transformations, filters are computed for smoothing photometric characteristic changes across the time-compressed video. Photometrically stabilized time-compressed video is generated from the time-compressed video by using the filters to smooth the photometric characteristic changes.

Photometric stabilization for time-compressed video

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Emeryville, CA, United States of America

Xuaner Zhang