WO2025047894A1 - Evaluation device - Google Patents

Abstract

This evaluation device includes a first acquisition unit, a second acquisition unit, and an evaluation unit. The first acquisition unit acquires first image data representing an original image which is to be evaluated for the presence or absence of copyright infringement. The second acquisition unit acquires a description describing the content of the original image by inputting the first image data into a trained model that has learned the relationship between image data and a description describing the content of an image represented by the image data. The evaluation unit evaluates the degree of probability of copyright infringement on the first image data on the basis of the number of words related to existing work, from among the words included in the description acquired by the second acquisition unit.

Description

Evaluation Equipment

The present invention relates to an evaluation device.

In virtual spaces such as the metaverse, various virtual objects are placed by the operators or users of the virtual space for the purpose of decoration or sale. It is anticipated that the relationship between the virtual objects placed in the virtual space and the copyrights of other people's works will become an issue. Patent Document 1 discloses a technology for avoiding copyright infringement. With this technology, when a virtual object contains a part that may infringe on the copyrights of others, image processing or other processing is performed to blur the relevant part.

JP 2016-082201 A

It is inefficient for a person to judge the possibility that a virtual object may infringe the copyright of an existing work, and there is also the problem that the standards for determining whether an infringement has occurred may differ depending on the judge's knowledge and subjectivity. This problem does not only arise in situations where the possibility of a virtual object infringing copyright is evaluated, but can also arise in situations where the possibility of an illustration or video posted on a posting site or the like infringing copyright is evaluated.

The evaluation device according to a preferred embodiment of the present disclosure has a first acquisition unit, a second acquisition unit, and an evaluation unit. The first acquisition unit acquires first image data representing an original image to be evaluated for the presence or absence of copyright infringement. The second acquisition unit acquires an explanatory text explaining the content of the original image by inputting the first image data into a learning model that has learned the relationship between image data and an explanatory text explaining the content of the image represented by the image data. The evaluation unit evaluates the degree of possibility of copyright infringement regarding the first image data based on the number of words related to existing works among the words included in the explanatory text acquired by the second acquisition unit.

According to the present disclosure, the degree of possibility of copyright infringement for existing works is evaluated based on a description generated from an image that is the subject of an evaluation of the degree of possibility of copyright infringement, making it possible to objectively and efficiently evaluate the degree of possibility of copyright infringement using certain standards.

1 is a diagram illustrating an example of a configuration of an evaluation device 10 according to an embodiment of the present disclosure. FIG. 2 is a diagram showing an example of the configuration of a record included in a management table TBL. FIG. 2 is a diagram showing an example of an original image and a derived image. 10 is a flowchart showing an example of an evaluation method executed by a processing device 160 of the evaluation device 10 according to a program PR1.

A. Embodiment FIG. 1 is a diagram showing an example of the configuration of an evaluation device 10 according to an embodiment of the present disclosure. The evaluation device 10 is a device that evaluates the degree of possibility that a three-dimensional virtual object installed in a virtual space such as a metaverse space by an operator or user of the virtual space infringes the copyright of an existing work. In this embodiment, the degree of possibility of copyright infringement of an existing work is evaluated using an image generated based on a virtual object that is to be evaluated for the degree of possibility of copyright infringement. An image generated based on a virtual object is an image obtained by capturing an image of a virtual object installed in a virtual space by a virtual camera installed in the virtual space. Hereinafter, a virtual object that is to be evaluated for the degree of possibility of copyright infringement is referred to as a target object. An image generated based on a target object is referred to as an original image.

As shown in FIG. 1, the evaluation device 10 includes a communication device 130, a storage device 150, a processing device 160, and a bus 190. The communication device 130, each of the storage devices 150, and the processing device 160 are connected to each other by the bus 190 for communicating information. The bus 190 may be configured using a single bus, or may be configured using different buses between each device.

The communication device 130 is hardware (transmitting/receiving device) for communicating with other devices via a communication line, either wired or wirelessly. The communication device 130 is also called, for example, a network device, a network controller, a network card, or a communication module. Examples of other devices that communicate with the communication device 130 via a communication line include a terminal device used by an operator of a virtual space, a terminal device used by a user, and a server that provides other communication services. A user who wishes to evaluate whether a target object infringes copyright can obtain an evaluation value indicating the degree of the possibility of copyright infringement by transmitting first image data representing an original image generated based on the target object from the terminal device used by the user to the evaluation device 10.

An example of a server that communicates with the communication device 130 via a communication line is a server 20 that stores a learning model 210 that has learned the relationship between image data and a description that explains the contents of the image shown by the image data. When the server 20 receives image data via a communication line, it recognizes objects that appear in the image represented by the image data. The server 20 then uses the learning model 210 to generate description data that represents a description of the recognized object, and returns the generated description data to the sender of the image data. Note that the learning model 210 generates a description using the formal name of the object for which the description is to be generated, even if the object for which the description is to be generated has multiple names, such as an abbreviation or a nickname in addition to the formal name.

The storage device 150 is a recording medium readable by the processing device 160. The storage device 150 includes, for example, a non-volatile memory and a volatile memory. The non-volatile memory includes, for example, a ROM (Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), or an EEPROM (Electrically Erasable Programmable Read Only Memory). The volatile memory is, for example, a RAM (Random Access Memory). The non-volatile memory of the storage device 150 stores a program PR1 that causes the processing device 160 to realize functions that prominently exhibit the characteristics of the present disclosure. The volatile memory of the storage device 150 is used as a work area when the processing device 160 executes the program PR1.

The storage device 150 also stores a management table TBL in advance. The management table TBL is a collection of multiple records. FIG. 2 is a diagram showing an example of the configuration of records included in the management table TBL. As shown in FIG. 2, one record includes a work identifier that uniquely identifies an existing work, a rights holder identifier that uniquely identifies the copyright holder of the work, and a group of related words. The work identifier is, for example, a character string that indicates the formal name of the work. The rights holder identifier is a character string that indicates the name or full name of the copyright holder. The group of related words is a collection of multiple words related to the work. Specific examples of words related to the work include words that indicate the formal name of the work, words that indicate the formal name of a character that appears in the work, words that indicate the external characteristics of the character (color, shape, gender, etc.), and words that indicate the name of a place related to the work (the location in the case of a work of a building, the name of the place where the movie is set in the case of a work of a movie, etc.).

The processing device 160 includes one or more central processing units (CPUs). The one or more CPUs are an example of one or more processors. Each of the processors and CPUs is an example of a computer. When the processing device 160 is instructed to execute program PR1 by an operation on an input device (not shown), the processing device 160 reads program PR1 from non-volatile memory to volatile memory. Then, the processing device 160 executes program PR1 read into volatile memory. The processing device 160 operating according to program PR1 functions as the first acquisition unit 160a, generation unit 160b, second acquisition unit 160c, and evaluation unit 160d shown in FIG. 1. In other words, the first acquisition unit 160a, generation unit 160b, second acquisition unit 160c, and evaluation unit 160d in FIG. 1 are software modules realized by operating the processing device 160 according to software. The functions of the first acquisition unit 160a, the generation unit 160b, the second acquisition unit 160c, and the evaluation unit 160d are as follows:

The first acquisition unit 160a acquires first image data representing an original image by communicating with a user's terminal device via a communication line. The generation unit 160b generates multiple second image data representing multiple derived images obtained by modifying the original image based on the first image data. The multiple second image data have a one-to-one correspondence with the multiple derived images. In this embodiment, the generation unit 160b generates 100 derived images, but the number of derived images generated by the generation unit 160b may be one or more.

Specific examples of modifications to an original image include changing the color of the surface of a target object appearing in the original image, adding or deleting a pattern from the target object, enlarging or reducing the target object, such as changing the proportions of the target object, deleting some components of the target object or adding new components, and combinations of these. FIG. 3 is a diagram showing an example of an original image and a derived image in this embodiment. For example, if the target object is a monster figurine and image G01 in FIG. 3 is the original image, images G02, G03, and G04 in FIG. 3 are examples of derived images. Image G02 is an image obtained by adding a polka dot pattern to the surface of the target object. Image G03 is an image obtained by reducing the proportions of the target object. Image G04 is an image obtained by removing the dorsal fin from the target object.

The second acquisition unit 160c acquires explanatory data relating to the original image by transmitting the first image data to the aforementioned server 20 via a communication line. The second acquisition unit 160c also acquires multiple explanatory data relating to multiple derived images by transmitting each of the multiple second image data to the aforementioned server 20. The multiple explanatory data have a one-to-one correspondence with the multiple derived images.

The evaluation unit 160d evaluates the degree of possibility of copyright infringement by the target object for each of the description data acquired by the second acquisition unit for each of the multiple images composed of the original image and multiple derived images. That is, in this embodiment, the degree of possibility of copyright infringement for the target object is evaluated based on the original image and multiple derived images. Evaluating the degree of possibility of copyright infringement using multiple derived images in addition to the original image is performed so that the degree of possibility of copyright infringement by the target object can be evaluated even if the target object has been intentionally altered with the aim of avoiding copyright infringement.

To explain in more detail, the evaluation unit 160d extracts words contained in the description by performing morphological analysis on the description represented by the description data acquired by the second acquisition unit 160c for each of the above-mentioned multiple images. The evaluation unit 160d evaluates the degree of possibility of copyright infringement for the target object based on the words extracted from the description and the related word group stored in the management table TBL for each copyrighted work.

As shown in FIG. 1, the evaluation unit 160d in this embodiment includes a determination unit 160d1 and a calculation unit 160d2. If a word included in a related word group related to any work is included in a plurality of words extracted from the description represented by the description data acquired by the second acquisition unit 160c for each of the above-mentioned plurality of images, the determination unit 160d1 determines that there is a possibility of copyright infringement for the work corresponding to the related word group. Conversely, if all of the plurality of words extracted from the description are not included in any of the related word groups, the determination unit 160d1 determines that there is no possibility of copyright infringement for an existing work.

The calculation unit 160d2 calculates an evaluation value representing the degree of possibility of copyright infringement by the target object based on the ratio between the number N of explanatory sentences determined by the determination unit 160d1 to be likely to infringe copyright and the total number M of explanatory sentences acquired by the second acquisition unit. In this embodiment, since M=101, when N=80, the calculation unit 160d2 calculates an evaluation value representing the degree of possibility of copyright infringement of 79.2%. The calculation unit 160d2 transmits the calculated evaluation value, the work identifier of the existing work determined to be likely to infringe copyright, and the right holder identifier associated with the work identifier to the sender of the first image data via a communication line.

Furthermore, the processing device 160 operating according to the program PR1 executes an evaluation method specific to the present disclosure. FIG. 4 is a flowchart showing the process flow of this evaluation method. As shown in FIG. 4, this evaluation method includes a first acquisition process SA110, a generation process SA120, a second acquisition process SA130, and an evaluation process SA140. The process contents of each process of the first acquisition process SA110, the generation process SA120, the second acquisition process SA130, and the evaluation process SA140 are as follows:

In the first acquisition process SA110, the processing device 160 functions as a first acquisition unit 160a. In the first acquisition process SA110, the processing device 160 acquires the first image data.

In the generation process SA120, the processing device 160 functions as a generating unit 160b. In the generation process SA120, the processing device 160 generates a plurality of second image data representing a plurality of derived images obtained by modifying the original image based on the first image data. In this embodiment, the processing device 160 generates 100 pieces of second image data representing different derived images.

In the second acquisition process SA130, the processing device 160 functions as a second acquisition unit 160c. In the second acquisition process SA130, the processing device 160 acquires explanatory text data by transmitting the first image data to the server 20 that stores a learning model 210 that has learned the relationship between the image data and explanatory text that explains the content of the image indicated by the image data. Also, in the second acquisition process SA130, the processing device 160 acquires multiple explanatory text data by transmitting multiple second image data generated in the generation process SA120 to the server. The multiple explanatory text data correspond one-to-one to the multiple derived images.

In the evaluation process SA140, the processing device 160 functions as an evaluation unit 160d. In the evaluation process SA140, the processing device 160 evaluates the degree of possibility of copyright infringement by the target object for each description acquired in the second acquisition process SA130 for each of the multiple images consisting of the original image and 100 derived images. The evaluation unit 160d determines whether or not there is copyright infringement based on the number of words related to existing works among the words contained in the description acquired by the second acquisition unit 160c for each of the multiple images consisting of the original image and 100 derived images. Next, the processing device 160 calculates an evaluation value that indicates the degree of possibility of copyright infringement by the target object based on the ratio between the number of descriptions determined to be likely to be copyright infringing and the total number of descriptions acquired in the second acquisition process SA130. Then, the processing device 160 transmits the calculated evaluation value, the work identifier of the existing work determined to be likely to be copyright infringing, and the right holder identifier to the sender of the first image data.

As described above, according to this embodiment, a description of a virtual object is generated from an image generated based on the virtual object to be evaluated for copyright infringement, and the degree of possibility of copyright infringement of an existing work is evaluated based on words contained in the description, making it possible to make an objective and efficient evaluation based on certain standards compared to when a person judges the presence or absence of infringement. Furthermore, according to this embodiment, the degree of possibility of copyright infringement for a virtual object is quantified as an evaluation value. Therefore, for virtual objects calculated to have an evaluation value equal to or greater than a predetermined threshold value (e.g., 70%), a detailed evaluation of the possibility of copyright infringement may be conducted by an expert.

B: Modifications The present disclosure is not limited to the above-described exemplary embodiments. Specific modifications are as follows. Two or more of the following exemplary embodiments may be combined.
B-1: Modification 1
The original image in the above embodiment is an image generated based on a three-dimensional virtual object, but the original image may be an image relating to a two-dimensional object, such as a painting, illustration, or an image of a cartoon character.

B-2: Modification 2
The generation of a derivative image is not essential, and the generation unit 160b may be omitted. In an aspect in which the generation unit 160b is omitted, the second acquisition unit 160c only needs to acquire a description for the original image, and the evaluation unit 160d only needs to evaluate the presence or absence of copyright infringement for an existing work based on the description for the original image. In addition, in an aspect in which the generation of a derivative image is omitted, the calculation unit 160d2 is not necessary. In other words, the evaluation of the degree of the possibility of copyright infringement according to the present disclosure includes a binary evaluation such as whether or not there is an infringement, in addition to a quantitative evaluation such as the calculation of the evaluation value in the above embodiment.

B-3: Modification 3
In the above embodiment, the first acquisition unit 160a, the generation unit 160b, the second acquisition unit 160c, and the evaluation unit 160d are software modules. However, any one, any two, any three, or all of the first acquisition unit 160a, the generation unit 160b, the second acquisition unit 160c, and the evaluation unit 160d may be hardware modules. Specific examples of hardware modules include DSPs (Digital Signal Processors), ASICs (Application Specific Integrated Circuits), PLDs (Programmable Logic Devices), and FPGAs (Field Programmable Gate Arrays). Even if any one, any two, any three, or all of the first acquisition unit 160a, the generation unit 160b, the second acquisition unit 160c, and the evaluation unit 160d are hardware modules, the same effects as those of the above embodiment are achieved.

B-4: Modification 4
In the above embodiment, the program PR1 is stored in the storage device 150 of the evaluation device 10, but the program PR1 may be manufactured or sold separately. The program PR1 may be provided to a purchaser, for example, by distributing a computer-readable recording medium such as a flash ROM on which the program PR1 is written, or by distributing the program PR1 by downloading it via a telecommunications line.

C: Others (1) In the above-described embodiment, ROM, RAM, etc. are given as examples of storage device 150, but storage device 150 may also be a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory device (e.g., a card, a stick, a key drive), a CD-ROM (Compact Disc-ROM), a register, a removable disk, a hard disk, a floppy (registered trademark) disk, a magnetic strip, a database, a server, or any other suitable storage medium.

(2) In the above-described embodiments, the information, signals, etc. described may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

(3) In the above-described embodiment, the input and output information, etc. may be stored in a specific location (e.g., memory) or may be managed using a management table. The input and output information, etc. may be overwritten, updated, or added to. The output information, etc. may be deleted. The input information, etc. may be transmitted to another device.

(4) In the above-described embodiment, the determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a comparison of numerical values (e.g., a comparison with a predetermined value).

(5) The order of the process steps, sequences, flow charts, etc. illustrated in the above-described embodiments may be changed as long as it is not inconsistent. For example, the methods described in this disclosure present elements of various steps using an example order and are not limited to the particular order presented.

(6) Each function illustrated in FIG. 1 is realized by any combination of at least one of hardware and software. Furthermore, there are no particular limitations on the method of realizing each functional block. That is, each functional block may be realized using one device that is physically or logically coupled, or may be realized using two or more devices that are physically or logically separated and connected directly or indirectly (e.g., using wires, wirelessly, etc.). A functional block may be realized by combining software with the one device or the multiple devices.

(7) The programs exemplified in the above-described embodiments should be broadly construed to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., regardless of whether software is called software, firmware, middleware, microcode, hardware description language, or by other names.

In addition, software, instructions, information, etc. may be transmitted and received via a transmission medium. For example, if the software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and/or wireless technologies (such as infrared, microwave, etc.), then at least one of these wired and wireless technologies is included within the definition of a transmission medium.

(8) In the above embodiments, the terms "system" and "network" are used interchangeably.

(9) The information, parameters, etc. described in this disclosure may be expressed using absolute values, may be expressed using relative values from a predetermined value, or may be expressed using other corresponding information.

(10) In the above-described embodiments, the mobile terminal may be a mobile station (MS). A mobile station may also be referred to by those skilled in the art as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable term. In addition, in this disclosure, terms such as "mobile station," "user terminal," "user equipment (UE)," and "terminal" may be used interchangeably.

(11) In the above-mentioned embodiments, the terms "connected" and "coupled" or any variation thereof refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access". As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using at least one of one or more wires, cables, and printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and light (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

(12) In the above embodiments, the term "based on" does not mean "based only on," unless otherwise specified. In other words, the term "based on" means both "based only on" and "based at least on."

(13) The terms "determining" and "determining" as used in this disclosure may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., searching in a table, database, or other data structure), ascertaining something as "judging" or "determining", etc. Also, "determining" and "determining" may include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), etc. Additionally, "judgment" and "decision" can include considering resolving, selecting, choosing, establishing, comparing, etc., to have been "judged" or "decided." In other words, "judgment" and "decision" can include considering some action to have been "judged" or "decided." Additionally, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

(14) In the above embodiments, when the terms "include," "including," and variations thereof are used, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, the term "or" as used in this disclosure is not intended to be an exclusive or.

(15) In this disclosure, where articles have been added by translation, such as a, an, and the in English, this disclosure may include that the noun following these articles is in the plural.

(16) In this disclosure, the term "A and B are different" may mean "A and B are different from each other." In addition, the term may mean "A and B are each different from C." Terms such as "separate" and "combined" may also be interpreted in the same way as "different."

(17) Each aspect/embodiment described in this disclosure may be used alone, in combination, or switched depending on the execution. In addition, notification of specific information (e.g., notification that "X is the case") is not limited to being done explicitly, but may be done implicitly (e.g., not notifying the specific information).

D: Aspects Understood from the Above-described Embodiments or Modifications Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure can be implemented as modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended as an illustrative example and does not have any limiting meaning on the present disclosure. The following aspects can be understood from at least one of the above-described embodiments or modifications.

The evaluation device according to the first aspect of the present disclosure has a first acquisition unit, a second acquisition unit, and an evaluation unit. The first acquisition unit acquires first image data representing an original image to be evaluated for the presence or absence of copyright infringement. The second acquisition unit acquires an explanatory text explaining the content of the original image by inputting the first image data into a learning model that has learned the relationship between image data and an explanatory text explaining the content of the image represented by the image data. The evaluation unit evaluates the degree of possibility of copyright infringement related to the first image data based on the number of words related to existing works among the words included in the explanatory text acquired by the second acquisition unit. According to the evaluation device of the first aspect, the degree of possibility of copyright infringement related to existing works can be efficiently evaluated according to a certain standard based on the first image data representing an original image to be evaluated for the presence or absence of copyright infringement.

The first image data in a second aspect (an example of the first aspect) of the present disclosure is generated based on a three-dimensional virtual object. The evaluation unit in the example of the second aspect evaluates the degree of possibility of copyright infringement by the virtual object. According to the second aspect, it is possible to evaluate the degree of possibility of copyright infringement by a three-dimensional virtual object.

The evaluation device according to the third aspect (an example of the second aspect) of the present disclosure includes a generation unit that generates, based on the first image data, one or more second image data representing one or more derived images obtained by modifying the original image. The second acquisition unit in the evaluation device according to the third aspect inputs the one or more second image data to the learning model to acquire one or more explanatory sentences that explain the contents of the one or more derived images. The one or more explanatory sentences correspond one-to-one to the one or more derived images. The evaluation unit in the evaluation device of the third aspect evaluates the degree of possibility of copyright infringement by the virtual object for each explanatory sentence acquired by the second acquisition unit for each of a plurality of images composed of the original image and the one or more derived images. According to the evaluation device of the fourth aspect, the degree of possibility of copyright infringement by the virtual object is evaluated, including the derived image obtained by modifying the original image. Therefore, even if the virtual object is intentionally modified to avoid copyright infringement, the degree of possibility of copyright infringement by the virtual object can be evaluated.

The evaluation unit in the evaluation device according to a fourth aspect (an example of the third aspect) of the present disclosure further includes a determination unit and a calculation unit. The evaluation unit determines whether or not there is a possibility of copyright infringement by the virtual object for each of the descriptions acquired by the second acquisition unit for each of the multiple images. The calculation unit calculates an evaluation value representing the degree of possibility of copyright infringement by the virtual object based on the ratio between the number of descriptions determined by the determination unit to have the possibility of copyright infringement and the total number of descriptions acquired by the second acquisition unit. According to the evaluation device of the fourth aspect, an evaluation value representing the degree of possibility of copyright infringement by the virtual object is calculated, and therefore the degree of possibility of copyright infringement by the virtual object is quantified.

10...Evaluation device, 130...Communication device, 150...Storage device, 160...Processing device, 160a...First acquisition unit, 160b...Generation unit, 160c...Second acquisition unit, 160d...Evaluation unit, 160d1...Determination unit, 160d2...Calculation unit, 190...Bus, PR1...Program, TBL...Management table.

Claims (4)

a first acquisition unit that acquires first image data representing an original image to be evaluated for the presence or absence of copyright infringement;
A second acquisition unit acquires an explanatory text explaining the content of the original image by inputting the first image data into a learning model that has learned a relationship between image data and an explanatory text explaining the content of the image represented by the image data;
an evaluation unit that evaluates a degree of possibility of copyright infringement regarding the first image data based on the number of words related to existing works among the words included in the description acquired by the second acquisition unit;
The evaluation device has The first image data is generated based on a three-dimensional virtual object;
The evaluation unit evaluates a degree of possibility of copyright infringement by the virtual object.
The evaluation device according to claim 1 . a generating unit configured to generate, based on the first image data, one or more second image data representing one or more derived images obtained by modifying the original image;
The second acquisition unit is
By inputting the one or more second image data into the learning model, one or more explanatory sentences explaining the contents of the one or more derived images are obtained;
the one or more legends correspond one-to-one to the one or more derived images;
The evaluation unit is
evaluating a degree of a possibility of copyright infringement by the virtual object for each of a plurality of images constituted by the original image and the one or more derived images, the description text being acquired by the second acquisition unit;
The evaluation device according to claim 2 . The evaluation unit is
a determination unit that determines whether or not there is a possibility of copyright infringement by the virtual object for each of the description sentences acquired by the second acquisition unit for each of the plurality of images;
a calculation unit that calculates an evaluation value that indicates a degree of a possibility of copyright infringement by the virtual object based on a ratio between the number of explanatory sentences determined by the determination unit to be likely to be copyright infringement and the total number of explanatory sentences acquired by the second acquisition unit,
The evaluation device according to claim 3 .

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