Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on POC values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: A battery pack includes a plurality of battery modules including module cases. Side surfaces of the module cases in which battery cells are accommodated face each other and a water injection hole is formed in a top surface of each of the module cases, and a fire extinguishing tank unit containing a fire extinguishing agent, located over the plurality of battery modules, and configured to supply the fire extinguishing agent only into a battery module in which a thermal event occurs from among the plurality of battery modules through the water injection holes.

Abstract: A battery pack includes a battery module having at least one battery cell, a control module connected to the battery module and configured to manage the battery module, a fire extinguishing tank containing a fire extinguishing agent and coupled to at least one of the battery module and the control module, and a side cover mounted on one side of the fire extinguishing tank and configured to guide electrical connection between the battery module and the control module.

Abstract: A battery pack ensures safety even when a thermal event occurs. A battery pack includes a battery module including one or more battery cells, a control module connected to the battery module to manage the battery module, and a fire extinguishing tank containing a fire extinguishing agent and coupled to at least one of the battery module and the control module.

Abstract: A battery pack includes a battery module including a water injection hole through which a fire extinguishing liquid can be supplied at an upper end portion and at least one drain hole through which the fire extinguishing liquid can be discharged at a lower end portion, a fire extinguishing tank unit containing the fire extinguishing liquid, located over the battery module, and configured to supply the fire extinguishing liquid to the battery module through the water injection hole, and a module supporter unit located under the battery module and supporting the battery module so that the battery module is located at a certain height from a ground. The module supporter unit includes a contaminated water storage container in which the fire extinguishing liquid dropping from the battery module through the drain hole is accommodated.

Abstract: Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.

Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on POC values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on picture order count (POC) values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on picture order count (POC) values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on picture order count (POC) values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.

Abstract: Provided are a video encoding method and apparatus having temporal scalability, and a video decoding method and apparatus having temporal scalability. The video encoding method includes: splitting pictures included in a picture sequence into temporal sub-layers; classifying, as a first temporal layer access picture or a second temporal layer access picture, a temporal layer access picture based on whether a picture encoded after the temporal layer access picture is capable of referring to a picture encoded before the temporal layer access picture; and adding, to transmission unit data including the temporal layer access picture, type syntax information for identifying the first temporal layer access picture and the second temporal layer access picture, wherein the picture encoded after the temporal layer access picture belongs to a same temporal sub-layer as the temporal layer access picture or belongs to an upper temporal sub-layer to the temporal layer access picture.

Abstract: Provided is in-loop filtering technology using a trained deep neural network (DNN) filter model. An image decoding method according to an embodiment includes receiving a bitstream of an encoded image, generating reconstructed data by reconstructing the encoded image, obtaining information about a content type of the encoded image from the bitstream, determining a deep neural network (DNN) filter model trained to perform in-loop filtering by using at least one computer, based on the information about the content type, and performing the in-loop filtering by applying the reconstructed data to the determined DNN filter model.

Abstract: Provided are an inter prediction method and a motion compensation method. The inter prediction method includes: performing inter prediction on a current image by using a long-term reference image stored in a decoded picture buffer; determining residual data and a motion vector of the current image generated via the inter prediction; and determining least significant bit (LSB) information as a long-term reference index indicating the long-term reference image by dividing picture order count (POC) information of the long-term reference image into most significant bit (MSB) information and the LSB information.

Abstract: Provided is an image encoding or decoding method and device capable of increasing image compression efficiency by determining a differential quantization parameter of a current block based on statistical information of original samples of the current block or samples reconstructed previously to the current block. The image decoding method includes receiving a bitstream, obtaining a predicted quantization parameter value and a quantized transformation coefficient of a current block from the bitstream, obtaining a differential quantization parameter of the current block based on statistical information of samples reconstructed previously to the current block, obtaining a quantization parameter of the current block based on the differential quantization parameter of the current block and the predicted quantization parameter value, and inversely quantizing the quantized transformation coefficient of the current block based on the quantization parameter of the current block.

Abstract: Provided is a prediction image generating technology using a deep neural network (DNN). Provided is an image decoding method including: receiving a bitstream of an encoded image; determining at least one block split from the encoded image; determining neighboring blocks for predicting a current block among the at least one block; generating prediction data of the current block by applying the neighboring blocks to a DNN learning model configured to predict a block of an image by using at least one computer; extracting residual data of the current block from the bitstream; and reconstructing the current block by using the prediction data and the residual data.

Abstract: Provided are an image compressing method including determining a compressed image by performing downsampling using a deep neural network (DNN) on an image; determining a prediction signal by performing prediction based on the compressed image; determining a residual signal based on the compressed image and the prediction signal; and generating a bitstream comprising information about the residual signal, wherein the DNN has a network structure that is predetermined according to training of a downsampling process using information generated in an upsampling process, and an image compressing device for performing the image compressing method. Also, provided are an image reconstructing method of reconstructing a compressed image by using a DNN for upsampling, the compressed image having been compressed by the image compressing method, and an image reconstructing device for performing the image reconstructing method.

Abstract: Provided is a method of encoding an image, the method including: determining a subjective quality of the image when the image is compressed; determining at least one degree of compression that changes the subjective quality and is from among degrees of compression indicating how much the image is compressed; and encoding the image by compressing a residual signal of the image, based on compression information according to the determined degree of compression, wherein the subjective quality is determined for each frame by using a Deep Neural Network (DNN). Provided are an image decoding method and an image decoding apparatus for performing the image decoding method for decoding an image by using information encoded according to an image encoding method.

Abstract: A method of determining a reference picture set (RPS), which is a set of reference pictures used in predictive decoding of a current picture that is to be decoded includes: obtaining a flag indicating whether the RPS is determined based on picture order count (POC) values of the current picture and a previous picture or whether the RPS is determined based on an index of a reference RPS, which is an identification value of the reference RPS that is one of pre-defined RPSs and is referred to in determining the RPS, and a delta RPS that is a difference value between a POC vale of a reference picture included in the reference RPS and a POC value of a reference picture included in the RPS; and determining the RPS according to a value of the flag.

Abstract: Provided is an image encoding or decoding method and device capable of increasing image compression efficiency by determining a differential quantization parameter of a current block based on statistical information of original samples of the current block or samples reconstructed previously to the current block. The image decoding method includes receiving a bitstream, obtaining a predicted quantization parameter value and a quantized transformation coefficient of a current block from the bitstream, obtaining a differential quantization parameter of the current block based on statistical information of samples reconstructed previously to the current block, obtaining a quantization parameter of the current block based on the differential quantization parameter of the current block and the predicted quantization parameter value, and inversely quantizing the quantized transformation coefficient of the current block based on the quantization parameter of the current block.