Samsung Electronics Co., Ltd.

Yonsei University

Aarhus Universitet

Other

Korea Advanced Institute of Science and Technology

Seoul National University

Carnegie Mellon University

Technische Universitat Munchen

Hyong Euk Lee

Inwoo Ha

Minsu Ahn

Seungin Park

Nahyup Kang

Donghoon Sagong

Jiyeon Kim

Minjung Son

Sang Hyun Kim

Keechang Lee

Qiang Wang

Chang Kyu Choi

Young Hun Sung

Seon Min Rhee

Yong Beom Lee

Yang Liu

Hao Wang

Kyung Hwan Kim

Sang Wook Kim

Sujin Lee

Weiming Li

Jung Bae Kim

Lin Ma

Byung In Yoo

Won-chul Bang

Sangwon Lee

Kee Chang Lee

Jinwoo Kim

Hui Zhang

Chao Zhang

Keun Woo Park

Dong Young Kim

Do Kyoon Kim

Jae Joon Han

Chul Hong Kim

Zhihua Liu

Shandong Wang

Yun-tae Kim

Jae Hyun Han

Hwiryong Jung

Heesae Lee

Kinam Kwon

Ji Yeon Kim

In Woo Ha

Min Su Ahn

Na Hyup Kang

Eunhee Kang

Won Chul Bang

Yueying Kao

Hee Sae Lee

Seon Joo Kim

Seung In Park

Jacob Toft Pedersen

Heewon Kim

Jae Seok Choi

Bho Ram Lee

Sanghyun Kim

Aswin C Sankaranarayanan

Kyoung Mu Lee

Lujin Gong

Tianhao Gao

Yamin Mao

Yeonkyung Lee

Anqi Yang

Gee Hyuk Lee

Toshiya Hachisuka

Mengyu Chu

Nils Thuerey

Dae Hwa Kim

Sung Geun Ahn

Junsang Yu

Hachisuka Toshiya

DongYoung Kim

Min-su Ahn

Inwoon Ha

Seong Kook Heo

A method and apparatus with noise consideration are provided. The method includes generating, using a noise model, a non-normal noise map corresponding to a noise of an input image, and generating an enhanced image of the input image by implementing an image enhancement model based on the input image and the non-normal noise map, where the noise of the input image follows a non-normal distribution.

Method and apparatus with noise consideration

A device with image acquisition includes: a first phase mask disposed at a front end of a display layer and configured to modulate external light; the display layer comprising pixel areas between hole areas through which the modulated light that has passed through the first phase mask passes; a second phase mask disposed at a rear end of the display layer and configured to modulate the modulated light that has passed through the first phase mask; an image sensor disposed at a rear end of the second phase mask and configured to generate a raw image by sensing the modulated light that has passed through the second phase mask; and a processor configured to perform image processing on the raw image, based on blur information corresponding to the raw image.

Method and apparatus with image quality improvement

An electronic device includes a processor configured to perform operations including inputting an image into an encoder to generate a feature map including information about an illumination present in the input image, iteratively updating a plurality of slot vectors using the calculated feature map to calculate a plurality of predicted illumination vectors, calculating, using the calculated plurality of predicted illumination vectors, a plurality of mixture maps representing respective effects of a plurality of virtual illuminations on pixels in the input image and a plurality of illumination color vectors representing respective color values of the plurality of virtual illuminations, and generating an illumination map using the calculated plurality of mixture maps and the calculated plurality of illumination color vectors.

Method and apparatus with white balancing

A method with image restoration includes: receiving an input image and a first task vector indicating a first image effect among candidate image effects; extracting a common feature shared by the candidate image effects from the input image, based on a task-agnostic architecture of a source neural network; and restoring the common feature to a first restoration image corresponding to the first image effect, based on a task-specific architecture of the source neural network and the first task vector.

Method and apparatus with image restoration

A method with image processing includes: setting an offset window for an offset pattern of a kernel offset and an offset parameter for an application intensity of the kernel offset; determining an output kernel by applying the kernel offset to an input kernel based on the offset window and the offset parameter; and adjusting contrast of a degraded image using the output kernel.

Method and apparatus with contrast adjustment

A method and apparatus with image correction is provided. A processor-implemented method includes generating, using a neural network model provided an input image, an illumination map including illumination values dependent on respective color casts by one or more illuminants individually affecting each pixel of the input image, and generating a white-adjusted image by removing at least a portion of the color casts from the input image using the generated illumination map.

Method and apparatus with image correction

A pose estimation method and apparatus is disclosed. The pose estimation method includes acquiring a raw image before a geometric correction from an image sensor, determining a feature point in the raw image, and estimating a pose based on the feature point.

Method and apparatus for estimating pose

An image acquisition apparatus includes a display layer including hole regions through which external light is received and pixel regions arranged between the hole regions, an image sensor disposed under the display layer and configured to generate a raw image by sensing the external light received through the hole regions, and a processor configured to perform image processing on the raw image based on blur information based on an arrangement of the hole regions.

Method and apparatus for image acquisition including image sensor

A method with image augmentation includes recognizing, based on a gaze of the user corresponding to the input image, any one or any combination of any two or more of an object of interest of a user, a situation of the object of interest, and a task of the user from partial regions of an input image determining relevant information indicating an intention of the user, based on any two or any other combination of the object of interest of the user, the situation of the object of interest, and the task of the user, and generating a visually augmented image by visually augmenting the input image based on the relevant information.

Method and apparatus with image augmentation

An image enhancement method, an image enhancement apparatus, and a method and apparatus for training the image enhancement apparatus are provided. The image enhancement apparatus may enhance a quality of a raw image captured by an under-display camera (UDC). The image enhancement apparatus may process the raw image for each channel according to characteristics of a photographing environment of the UDC. The image enhancement apparatus may further enhance the image by processing the raw image to reflect characteristics for each channel.

Image enhancement method, image enhancement apparatus, and method and apparatus for training image enhancement apparatus

Provided are methods and apparatuses for determining a target object in an image based on an interactive input. A target object determining method acquires first feature information corresponding to an image and second feature information corresponding to an interactive input; and determines a target object corresponding to the interactive input from among objects in the image based on the first feature information and the second feature information.

Method and apparatus for determining target object in image based on interactive input

A modeling method searches for a sequence matched to a user input using a fluid animation graph generated based on similarities among frames included in sequences included in the fluid animation graph and models a movement corresponding to the user input based on a result of the searching. Provided also is a corresponding apparatus and a method for preprocessing for such modeling.

Modeling method and apparatus and apparatus using fluid animation graph

An image processing apparatus includes a first processor configured to obtain, from a color image, an illumination element image and an albedo element image corresponding to the color image, and a second processor configured to divide the illumination element image into a plurality of subelement images each corresponding to the color image.

Image processing apparatus and method

An object detection method includes setting a first window region and a second window region larger than the first window region that correspond to partial regions of different sizes in an input image, downsampling the second window region to generate a resized second window region, detecting a first object candidate from the first window region and a second object candidate from the resized second window region, and detecting an object included in the input image based on one or both of the first object candidate and the second object candidate.

Method and apparatus for detecting object

A method and apparatus for predicting an object of interest of a user receives an input image of a visible region of a user and gaze information including a gaze sequence of the user, generates weight filters for a per-frame segmentation image by analyzing a frame of the input image for input characteristics of the per-frame segmentation image and the gaze information, and predicts an object of interest of the user by integrating the weight filters and applies the integrated weight filter to the per-frame segmentation image.

Method and apparatus for predicting object of interest of user

Growing community of inventors

Suwon-si, South Korea

Hyong Euk Lee