Qualcomm Incorporated

Reza Pourreza Shahri

Ramin Rezaiifar

Taco Sebastiaan Cohen

Amir Said

Alexei Vladimirovich Bourd

Amirhossein Habibian

Auke Joris Wiggers

Dam Backer

Brian Ellis

Donna Roy

Dana Kianfar

Shuaib Uddin Arshad

Mona Fathollahi Ghezelghieh

Roman Larionov

Li He

Vaibhav Rajesh Gandhi

A video encoder determines scaled transform coefficients, wherein determining the scaled transform coefficients comprises scaling transform coefficients of a block of the video data according to a given quantization step. The video encoder determines scalar quantized coefficients, wherein determining the scalar quantized coefficients comprises applying scalar quantization to the scaled transform coefficients of the block. Additionally, the video encoder applies a neural network that determines a respective set of probabilities for each respective transform coefficient of the block. The respective set of probabilities for the respective transform coefficient includes a respective probability value for each possible adjustment value in a plurality of possible adjustment values. Inputs to the neural network include the scaled transform coefficients and the scalar quantized coefficients. The video encoder determines, based on the set of probabilities for a particular transform coefficient of the block, a quantization level for the particular transform coefficient.

Parallelized rate-distortion optimized quantization using deep learning

The present disclosure relates to methods and apparatus for graphics processing. The apparatus can obtain at least one input image including a plurality of pixels. Additionally, the apparatus can determine shading information for each of the plurality of pixels in the at least one input image. The apparatus can also determine a shading map based on the determined shading information for each of the plurality of pixels in the at least one input image. In some aspects, the apparatus can generate at least one output image based on the at least one input image and the determined shading map. The apparatus can also enhance a quality of the at least one output image. In some aspects, the quality of the at least one output image can be enhanced based on machine learning. Further, the apparatus can generate the at least one input image including the plurality of pixels.

Methods and apparatus for machine learning rendering

Systems, methods, and computer-readable media are provided for transferring color information from a no-flash image of a scene to a flash image of the scene using a localized tonal mapping algorithm. In some aspects, an example method can include obtaining a no-flash image and a flash image, mapping color information from the no-flash image to the flash image, and generating an output image including the flash image modified based on the mapping to include at least a portion of the color information from the no-flash image.

Systems and methods for color matching for realistic flash images

The present disclosure relates to methods and devices for facilitating enhancing the quality of video. An example method disclosed herein includes estimating an optical flow between a first noisy frame and a second noisy frame, the second noisy frame following the first noisy frame. The example method also includes warping a first enhanced frame to align with the second noisy frame, the warping being based on the estimation of the optical flow between the first noisy frame and the second noisy frame, the first enhanced frame being an enhanced frame of the first noisy frame. The example method also includes generating a second enhanced frame based on the warped first enhanced frame and the second noisy frame, and outputting the second enhanced frame.

Methods and apparatus to facilitate enhancing the quality of video

Techniques and systems are provided for processing one or more low light images. For example, a short exposure image associated with one or more shutter speeds can be obtained. A long exposure image is also obtained, which is captured using a slower shutter speed than the one or more shutter speeds associated with the short exposure image. An output image can be generated by mapping color information from the long exposure image to the short exposure image.

Systems and methods for processing low light images

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San Diego, CA, United States of America

Reza Pourreza Shahri