Electronics and Telecommunications Research Institute

Sejong University

Industry-university Cooperation Foundation Korea Aerospace University

Korea University Research and Business Foundation

Ji-Hoon Do

Tae-Jin Lee

Se-Yoon Jeong

Dong-Hyun Kim

Jin-Soo Choi

Hyoung-Jin Kwon

Joo-Young Lee

Youn-Hee Kim

Jong-Ho Kim

Jin-Ho Lee

Ha-Hyun Lee

Yung-Lyul Lee

Sung-Chang Lim

Seoung-Jun Oh

Jae-Gon Kim

Hui-Yong Kim

Dong-Gyu Sim

Do-Hyeon Park

Yong-Uk Yoon

Min-Hun Lee

Jee-Hoon Kim

Kwang-Hwan Kim

Han-Sol Choi

Jung-Won Kang

Yun-gu Lee

Gun Bang

Seong-Jun Bae

Seung-won Jung

Dong-Wook Kim

Soo-Woong Kim

Yun-Gu Lee

Disclosed herein are a method, an apparatus, and a storage medium for image encoding/decoding using filtering. The image encoding method and the image decoding method perform classification on a classification unit of a target image, and perform filtering that uses a filter on the classification unit. A classification index of the classification unit is determined, and the classification index indicates a filter to be used for filtering on the classification unit, among multiple filters. The classification index is determined by various coding parameters, such as an encoding mode of the target block and an encoding mode of a neighboring block adjacent to the target block.

Method, apparatus and storage medium for image encoding/decoding using filtering

Disclosed herein is a method for generating a texture map of a 3D mesh includes encoding a texture map of a 3D mesh, quantizing the encoded texture map, decoding the quantized texture map, performing rendering using the decoded texture map, and updating the texture map of the 3D mesh based on the value of a loss function.

Apparatus and method for generating texture map of 3-dimensional mesh

There are provided a method, apparatus, system, and computer-readable recording medium for image compression. An encoding apparatus performs domain transformation and quantization on feature map information and image information. The encoding apparatus rearranges the result of domain transformation and quantization so as to have a form advantageous to the encoding procedure and encodes the result of rearrangement, thereby generating a bitstream. A decoding apparatus receives the bitstream, decodes the received bitstream, and performs inverse transformation, dequantization, and inverse rearrangement using information transmitted through the bitstream. The result of inverse transformation, dequantization, and inverse rearrangement is used for the machine-learning task of a neural network.

Method, apparatus, system and computer-readable recording medium for feature information

Disclosed herein are a method, an apparatus, and a storage medium for image encoding/decoding. An intra-prediction mode for the target block is derived, and intra-prediction for the target block that uses the derived intra-prediction mode is performed. The intra-prediction mode for the target block is derived using an artificial neural network, and an MPM list for the target block is derived using information about the target block, pieces of information about blocks adjacent to the target block, and the artificial neural network. The artificial neural network outputs one or more available intra-prediction modes. Further, the artificial neural network outputs match probabilities for one or more candidate intra-prediction modes, and each of the match probabilities for the candidate intra-prediction modes indicates a probability that the corresponding candidate intra-prediction mode matches the intra-prediction mode for the target block.

Apparatus, method and storage medium for image encoding/decoding to perform intra prediction using artificial neutral network

There are provided an apparatus, method, system, and recording medium for performing selective encoding/decoding on feature information. An encoding apparatus generates residual feature information. The encoding apparatus transmits the residual feature information to a decoding apparatus through a residual feature map bitstream. The residual feature information is the difference between feature information extracted from an original image and feature information extracted from a reconstructed image. Feature information of the reconstructed image is generated using the reconstructed image. Reconstructed feature information is generated using the feature information of the reconstructed image and reconstructed residual feature information.

Disclosed herein are a method, an apparatus and a storage medium for image encoding/decoding using a binary mask. An encoding method includes generating a latent vector using an input image, generating a selected latent vector component set using a binary mask, and generating a main bitstream by performing entropy encoding on the selected latent vector component set. A decoding method includes generating a selected latent vector component set including one or more selected latent vector components by performing entropy decoding on a main bitstream and generating the latent vector in which the one or more selected latent vector components are relocated by relocating the selected latent vector component set in the latent vector.

Method, apparatus and storage medium for image encoding/decoding using binary mask

Disclosed herein are a decoding method and apparatus and an encoding method and apparatus for deriving an intra-prediction mode. An intra-prediction mode may be derived using a method for deriving an intra-prediction mode based on a neighbor block of the target block, a method for deriving an intra-prediction mode using signaling of the intra-prediction mode of the target block, or a method for deriving an adaptive intra-prediction mode based on the type of a target slice. An MPM list may be used to derive the intra-prediction mode, and a temporal neighbor block or the like may be used to configure the MPM list.

Method and apparatus for deriving intra prediction mode

Disclosed herein are a method, apparatus, system, and computer-readable recording medium for image compression. An encoding apparatus performs preprocessing of feature map information, frame packing, frame classification, and encoding. A decoding apparatus performs decoding, frame depacking, and postprocessing in order to reconstruct feature map information. By encoding the feature map information, inter-prediction and intra-block prediction for a frame are performed. The encoding apparatus provides the decoding apparatus with a feature map information bitstream for reconstructing the feature map information along with an image information bitstream.

Method, apparatus, system and computer-readable recording medium for feature map information

Disclosed herein are a decoding method and apparatus and an encoding method and apparatus for deriving an intra prediction mode. An intra prediction mode may be derived using a method for deriving an intra prediction mode based on a neighbor block of the target block, a method for deriving an intra prediction mode using signaling of the intra prediction mode of the target block, or a method for deriving an adaptive intra prediction mode based on the type of a target slice. An MPM list may be used to derive the intra prediction mode, and a temporal neighbor block or the like may be used to configure the MPM list.

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Busan, South Korea

Ji-Hoon Do