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公开(公告)号：US20240203161A1
公开(公告)日：2024-06-20
申请号：US18535420
申请日：2023-12-11
发明人： Ju Hong YOON , Min Gyu PARK , Yong Hoon KWON , Je Woo KIM
IPC分类号： G06V40/16 , G06V10/774 , G06V10/776 , G06V10/778 , G06V40/40
CPC分类号： G06V40/174 , G06V10/774 , G06V10/776 , G06V10/7788 , G06V40/169 , G06V40/40 , G06V10/82
摘要： There is provided an emotion prediction method based on virtual facial expression image augmentation. The emotion prediction method may acquire a user facial image, may extract a facial expression feature from the acquired user facial image, and may predict a user emotion from the extracted facial expression feature. The emotion prediction method may extract the facial expression feature by using a facial expression recognition network, the facial expression recognition network being an AI model that is trained to receive a user facial image and to extract a facial expression feature. The facial expression recognition network is retrained with virtual facial images which are augmented from a facial image that causes a failure in emotion recognition. Accordingly, by augmenting features of a facial expression image that causes a failure in prediction through error feedback, facial expression recognition performance can be enhanced.
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公开(公告)号：US20240212267A1
公开(公告)日：2024-06-27
申请号：US18539462
申请日：2023-12-14
发明人： Min Gyu PARK , Ju Hong YOON , Ju Mi KANG , Je Woo KIM
摘要： There are provided an apparatus and a method for reconstructing a 3D human object based on a monocular image through depth image-based implicit function learning. A 3D human object reconstruction method according to an embodiment includes: predicting a double-sided orthographic depth map from a front perspective color image of a human object; predicting a signed distance (SD) regarding points on a 3D space from the predicted double-sided orthographic depth map; and reconstructing a 3D human object by using the predicted SD. Accordingly, a human object and details can be naturally reconstructed with respect to not only an area visible through a front perspective color image of the human object but also an invisible area.
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公开(公告)号：US20240202951A1
公开(公告)日：2024-06-20
申请号：US18539832
申请日：2023-12-14
发明人： Min Gyu PARK , Ju Hong YOON , Min Ho LEE , Je Woo KIM
IPC分类号： G06T7/593 , G01S17/89 , G06V10/771
CPC分类号： G06T7/593 , G01S17/89 , G06V10/771 , G06T2207/20081
摘要： There is provided a depth estimation method for a small baseline-stereo camera through LiDAR sensor fusion. A depth map estimation method according to an embodiment may estimate a high-resolution depth map from a small baseline-stereo image based on deep learning, by using transfer learning from a deep learning network that is trained to estimate a depth map from a wide baseline-stereo image. Accordingly, in a device which has a small baseline-stereo camera installed therein due to structural constraints, such as a smartphone, a wearable AR/VR device, a drone, 3D image quality can be enhanced. In addition, according to embodiments, pseudo-LiDAR data may be generated by using a depth map estimated from a small baseline-stereo image, and may be used for replacing or reinforcing LiDAR data.
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公开(公告)号：US20210334553A1
公开(公告)日：2021-10-28
申请号：US17137832
申请日：2020-12-30
发明人： Min Gyu PARK , Ju Hong YOON , Je Woo KIM
摘要： A method and an apparatus for detecting a lane is provided. The lane detection apparatus according to an embodiment includes: an acquisition unit configured to acquire a front image of a vehicle; and a processor configured to input the image acquired through the acquisition unit to an AI model, and to detect information of a lane on a road, and the AI model is trained to detect lane information that is expressed in a plane form from an input image. Accordingly, data imbalance between a lane area and a non-lane area can be solved by using the AI model which learns/predicts lane information that is expressed in a plane form, not in a segment form such as a straight line or curved line.
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