Abstract: An image processing device configured to obtain difference maps between a first frame or a first feature map corresponding to the first frame, and second feature maps corresponding to a second frame, obtain third feature maps and fourth feature maps by performing pooling processes on the difference maps according to a first size and a second size, obtain modified difference maps by weighted-summing the third feature maps and the fourth feature maps, identify any one collocated sample based on sizes of sample values of collocated samples of the modified difference maps corresponding to a current sample of the first frame, and determine a filter kernel used to obtain the second feature map corresponding to the modified difference map including the identified collocated sample, as a motion vector of the current sample.

Abstract: An image processing method for artificial intelligence (AI)-based filtering includes: obtaining motion information regarding inter prediction of a current block of a current reconstructed image, based on the motion information regarding the inter prediction, determining at least one reference reconstructed image regarding the current reconstructed image, based on the motion information and the at least one reference reconstructed image, determining at least one reference block, by inputting the current block and the at least one reference block to a neural network, obtaining an output block corresponding to the current block, and based on the output block, obtaining a modified current reconstructed image, wherein the neural network is trained using training data including the current block, the at least one reference block, and the output block, to reduce an error between the current block and an original block corresponding to the current block.

Abstract: A method, performed by an image decoding apparatus, of decoding a motion vector, including obtaining information indicating a motion vector resolution of a current block from a bitstream; selecting a first neighboring block from among neighboring blocks adjacent to the current block, by using the obtained information indicating the motion vector resolution of the current block; based on the current block referring to a reference picture in a list 0, and the first neighboring block referring to the reference picture in the list 0, determining a prediction motion vector of the current block using a motion vector of the first neighboring block; based on the current block referring to the reference picture in the list 0 and the first neighboring block referring to a reference picture in a list 1, selecting a motion vector of a second neighboring block among the neighboring blocks as a basic motion vector, and determining the prediction motion vector of the current block using the determined basic motion vector; a

Abstract: An artificial intelligence (AI)-based image decoding method and an apparatus performing the AI-based image decoding method are provided. According to the AI-based image decoding method, a transform block for a residual block of a current block is obtained from a bitstream, a transform kernel for the transform block is generated by applying, to a neural network, a prediction block for the current block, neighboring pixels of the current block, and coding context information, the residual block is obtained by applying the generated transform kernel to the transform block, and the current block is reconstructed by using the residual block and the prediction block.

Abstract: Provided is a video decoding method including obtaining identification information of a first tile and identification information of a last tile from a bitstream, wherein the first and last tiles are included in a first slice, determining an index difference between the first tile and the last tile, based on a result of comparing the identification information of the first tile with the identification information of the last tile, determining the number of tiles included in the first slice, by using the index difference between the first tile and the last tile, and decoding a plurality of tiles included in the first slice according to an encoding order by using the number of tiles included in the first slice, the identification information of the first tile, and the identification information of the last tile.

Abstract: Provided are an image decoding method and apparatus.

Abstract: An image encoding method based on artificial intelligence (AI) includes obtaining motion vector feature data of a current frame by inputting the current frame and a reference frame to a motion vector encoder and applying a plurality of resolution scales to the current frame and the reference frame via the motion vector encoder; obtaining a current motion vector by inputting the motion vector feature data to a motion vector decoder; obtaining a current predicted image based on the current motion vector and the reference frame; and generating a bitstream based on the motion vector feature data and the current predicted image.

Abstract: An organic light emitting display device and a method for providing low luminance power thereof includes a data driver including a lookup table storing therein a low potential voltage and an initialization voltage corresponding to each gamma set such that a low potential voltage and an initialization voltage in a 60 Hz operation mode are respectively different from a low potential voltage and an initialization voltage in a 90 Hz operation mode and a method compensates for an anode charging time in the low luminance range, thereby improving seamlessness.

Abstract: An organic light emitting display device and a method for providing low luminance power thereof includes a data driver including a lookup table storing therein a low potential voltage and an initialization voltage corresponding to each gamma set such that a low potential voltage and an initialization voltage in a 60 Hz operation mode are respectively different from a low potential voltage and an initialization voltage in a 90 Hz operation mode and a method compensates for an anode charging time in the low luminance range, thereby improving seamlessness.

Abstract: Disclosed are an organic light emitting display device and a method for providing low luminance power thereof, in which a low potential voltage and an initialization voltage are provided to a display panel in a low luminance range such that a low potential voltage and an initialization voltage in a 60 Hz operation mode are respectively different from a low potential voltage and an initialization voltage in a 90 Hz operation mode. To this end, the device includes a data driver including a lookup table storing therein a low potential voltage and an initialization voltage corresponding to each gamma set such that a low potential voltage and an initialization voltage in a 60 Hz operation mode are respectively different from a low potential voltage and an initialization voltage in a 90 Hz operation mode. Therefore, the method compensates for an anode charging time in the low luminance range, thereby improving seamlessness.