DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 07/07/2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Regarding claims 1 and 18-20, claim limitation “determining, for a conversion between a video unit of a video and a bitstream of the video, a neural-network post-filter (NNPF) is activated” is unclear as to whether the determination is of which neural-network post-filter is activated or that a neural-network post-filter is activated. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b). Furthermore, this claim will be interpreted to mean that a neural-network post-filter is activated.
Regarding claim 12, claim limitation “wherein pictures are interpolated between a pair of consecutive input pictures and an indentification of the pair is indicated ” is unclear as to what an indentification would be for a pair. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b). Furthermore, this claim will be interpreted to mean an identification.
Regarding claim 15, claim limitation “the default value” is declared as if referring to an antecedent, but the antecedent in claim 14 is not a required limitation but an optional one. Therefore the antecedent basis is ambiguous and unclear. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b).
Claim(s) 2-11, 13-14, and 16-17 is/are rejected for their dependence on claim(s) 1, 12, and 15, because they do not contain additional language that would overcome the indefiniteness issues recited with regard to those claims.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Deshpande et al. (US 20240372997) (hereinafter Deshpande).
Regarding claim 20, this claim is directed to a non-transitory computer-readable medium storing a bitstream generated by a method. Significantly, the claimed non-transitory computer readable medium is not implementing any method; no instructions/steps are being executed. Instead, the claimed storage medium merely stores the data output from and/or generated by a method. In other words, these claims are directed to a mere machine-readable medium storing data content (a bitstream generated by an method).
Applicant seeks to patent the storage of a bitstream in the abstract. In other words, the claim seeks to patent the content of the information (bitstream with video content) and not the process itself. Moreover, this stored bitstream does not impose any definitive physical organization on the data as there is no functional relationship between the bitstream and the storage medium. In conclusion, this claim is directed to mere data content (bitstream generated by the recited method) stored as a bitstream on a computer-readable storage medium. Under MPEP 2111.05(III), such claims are merely machine-readable media. Furthermore, there is no disclosed or claimed functional relationship between the stored data and medium. Instead, the medium is merely a support or carrier for the data being stored. Therefore, the data stored and the way such data is generated should not be given patentable weight. See MPEP 2111.05 applying In re Lowry, 32 F.3d 1579, 1583-84, 32 USPQ2d 1031, 1035 (Fed. Cir. 1994) and In re Ngai, 367 F.3d 1336, 70 USPQ2d 1862 (Fed. Cir. 2004). As such, this claim is subject to a prior art rejection based on any non-transitory computer readable medium known before the earliest effective filing date of the present application. Therefore, this claim is anticipated by Deshpande, as Deshpande paragraphs 2 and 7 discloses a computer readable medium storing a coded bitstream.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically taught as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Deshpande et al. (US 20240372997) (hereinafter Deshpande) in view of Hannuksela (US 20160212439) (hereinafter Hannuksela).
Regarding claim 1, Deshpande teaches A method for video processing, comprising:
determining, for a conversion between a video unit of a video and a bitstream of the video, a neural-network post-filter (NNPF) is activated for a set of pictures related to the video unit; apply the NNPF to one or more pictures in the set of pictures according to an order (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela); and
However, Deshpande does not explicitly teach conversion as needed for the limitations of claim 1.
Hannuksela, in a similar field of endeavor, teaches performing the conversion based on output of the NNPF (see Hannuksela paragraph 473 regarding data format conversion- in combination with Deshpande, which teaches methods for NNPF application, the end output conversion and coding may be performed by the conversion of Hannuksela).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to modify the teaching of Deshpande to include the teaching of Hannuksela so that in combination with Deshpande, which teaches methods for NNPF application, the end output conversion and coding may be performed by the conversion of Hannuksela.
One would be motivated to combine these teachings in order to provide methods for encoding and decoding video that improve conversion and coding efficiency (see Hannuksela paragraph 473).
Regarding claim 2, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 1, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the NNPF is applied to each picture in the set of pictures in an output order of pictures in the set of pictures, and the NNPF is applied to one picture at a time (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 3, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 1, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein if the NNPF takes one picture as input, and if the NNPF is applied to a current picture for which the NNPF is activated, an input picture of the NNPF is the current picture (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 4, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 1, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein pictures which are used as input pictures of the NNPF are determined, or wherein pictures which are used as input pictures of the NNPF are specified, or wherein pictures which are used as input pictures of the NNPF are indicated, and wherein the input pictures are specified and listed in output order (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 5, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 4, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein one or more pictures before the current picture are listed in output order, and one or more pictures after the current picture are listed in output order (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 6, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 5, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein one or more pictures before the current picture are listed in decoding order, one or more pictures after the current picture are listed in output order, and/or wherein one or more pictures before the current picture are listed in output order, one or more pictures after the current picture are listed in decoding order, and/or wherein one or more pictures before the current picture are listed in decoding order, and one or more pictures after the current picture are listed in decoding order (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 7, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 4, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein one or more identifications related to the pictures which are used as input are indicated (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 8, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 7, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein each picture order count (POC) value of the input pictures is indicated, and/or wherein a difference related to POC values in the input pictures are indicated (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 9, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 8, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein a POC difference between each input picture and a picture for which the NNPF is activated is indicated, and/or wherein a least POC value in the input pictures is indicated, and a difference between a rest POC value and the least POC value is indicated, and/or wherein a largest POC value in the input pictures is indicated, and a difference between a rest POC value and the largest POC value is indicated, and/or wherein a medium POC value in the input pictures is indicated, and a difference between a rest POC value and the medium POC value is indicated (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 10, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 1, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the NNPF is applied to each picture in the set of pictures in a decoding order of pictures in the set of pictures, and the NNPF is applied to one picture at a time, and/or wherein the NNPF is applied to each group comprising a fixed number of consecutive pictures in the set of pictures in a decoding order of pictures in the set of pictures, and the NNPF is applied to one group at a time, and/or wherein the NNPF is applied to each group comprising a fixed number of consecutive pictures in the set of pictures in an output order of pictures in the set of pictures, and the NNPF is applied to one group at a time, and/or wherein for an NNPF purpose of picture rate upsampling, one or more pictures are interpolated between one pair of input pictures, even if more than two input pictures are utilized for the interpolation, and/or wherein for an NNPF purpose of picture rate upsampling, one or more pictures are interpolated between a middle pair of input pictures, even if more than two input pictures are utilized for the interpolation, and/or wherein interpolated pictures generated by a post-processing filter are specified, or the interpolated pictures generated by the NNPF are indicated, and/or wherein a padding approach is used for generation of unavailable input pictures, and/or wherein unavailable pictures are interpolated with existing available pictures (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 11, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 10, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein a syntax of an post-filter characteristics (NNPFC) supplemental enhancement information (SEI) message requires that each of an i-th NNPFC interpolated pictures which is represented as nnpfc interpolatedpics[i ] is greater than 0 for only one of the i in the range of 0 to NNPFC number of input pictures minus two which is represented as inclusive, wherein i is an integer number, and/or wherein a syntax of an NNPFC SEI message requires that each of an i-th NNPFC interpolated pictures which is represented as nnpfc interpolatedpics[ i ] is greater than 0 for only if i is equal to 0 to NNPFC number of input pictures minus two divided by 2 which is represented as nnpfc num inputicsminus2/2, wherein i is an integer number, and/or wherein only one instance of i-th NNPFC interpolated pictures which is represented as nnpfc_interpolated_pics[ i ] is indicated in an NNPFC SEI message, and/or wherein nnpfc_num_input_pics_minus2 is an even number, and the middle pair of input pictures are the nnpfc_num_input_pics_minus2/2-th input picture and the (nnpfc_num_input_pics_minus2/2+1)-th input picture, and/or wherein one or more syntax elements are indicated to specify the interpolated pictures, and/or wherein the interpolated pictures are determined based on input pictures (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 12, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 11, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the i-th NNPFC interpolated pictures is equal to 0 for all other values of i, and/or wherein a syntax element which is represented as nnpfc_interpolated_pics_minus1 is indicted in the NNPFC SEI message, and wherein nnpfc_interpolated_pics_minus1 plus 1 specifies the number of interpolated pictures between the middle pair of input pictures, and/or wherein a least POC value and a largest POC value of the interpolated pictures are indicated, and/or wherein a least POC value of the interpolated pictures is indicated, and a largest POC value of the interpolated pictures is derived based on the number of interpolated pictures which is indicated in an NNPFC SEI message, and/or wherein the interpolated pictures are between the middle pair of input pictures, and/or wherein the interpolated pictures are between a first pair of input pictures, and/or wherein the interpolated pictures are between a last pair of input pictures, and/or wherein pictures are interpolated between a pair of consecutive input pictures and an indentification of the pair is indicated (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 13, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 12, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the input pictures with the index of [N/2] and [N/2]+ 1 comprises the middle pair of input pictures, wherein N is an integer number and represents the number of input pictures and [x] represents a greatest integer less than or equal to x, and/or wherein POC values of input pictures in the pair are indicated, and/or wherein an index of a first input picture in the pair is indicated (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 14, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 10, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the unavailable pictures are replaced with closest available picture in an order of decoding order, and/or wherein the unavailable pictures are replaced with available picture with a lowest quantization parameter (QP) in an order of decoding order, and/or wherein the unavailable pictures are padded with a default value, and/or wherein a bilinear filter is used for interpolation of the unavailable pictures, and/or wherein a bicubic filter is used for interpolation of the unavailable pictures, and/or wherein a Lanczos filter is used for interpolation of the unavailable pictures, and/or wherein a neural network based interpolation filter is used for interpolation of the unavailable pictures (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Regarding claim 15, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 14, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the default value is normalized, and/or wherein the default value is not normalized and in a range from 0 to N-1, inclusive, where N is an integer (see Hannuksela paragraphs 280 and 288 regarding default values for unavailable pictures and setting the default value to 0- in combination with Deshpande, the default value of the unavailable pictures may be padded to 0).
One would be motivated to combine these teachings in order to provide methods for encoding and decoding video that improve conversion and coding efficiency (see Hannuksela paragraph 473).
Regarding claim 16, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 15, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the default value is 0, or wherein the default value is 0.5, or wherein the default value is 1, and/or wherein the N is specified to 1 «(nnpfc_inp_tensor_bitdepth_minus8+8) (see Hannuksela paragraphs 280 and 288 regarding default values for unavailable pictures and setting the default value to 0- in combination with Deshpande, the default value of the unavailable pictures may be padded to 0).
One would be motivated to combine these teachings in order to provide methods for encoding and decoding video that improve conversion and coding efficiency (see Hannuksela paragraph 473).
Regarding claim 17, the combination of Deshpande and Hannuksela teaches all aforementioned limitations of claim 1, and is analyzed as previously discussed.
Furthermore, the combination of Deshpande and Hannuksela teaches wherein the conversion includes encoding the video unit into the bitstream, or wherein the conversion includes decoding the video unit from the bitstream (see Deshpande paragraphs 3, 29, 150-183, 216, and 257 regarding input pictures with picture order count identifiers being sequentially input into an NNPF, with one current picture at a time, with the picture order being identified and determined for an output order and decoding order, and values of the POC are known with respect to the difference between the current picture and NNPF applied values, NNPF is applied to pictures in a group in an output order of pictures, interpolated pictures are based on input pictures eventually becoming output pictures where pictures are interpolated, and interpolated pairs may be identified, and a neural network interpolation is used, and the conversion includes encoding a video into a bitstream and decoding it- in combination with Hannuksela below, the NNPF methods of Deshpande may be performed and then converted according to the conversion teachings of Hannuksela).
Independent claim(s) 18-20 is/are analogous in scope to claim(s) 1, albeit regarding a processor, non-transitory memory/medium, instructions and/or a bitstream as taught by Deshpande paragraphs 2 and 7, and is/are rejected according to the same reasoning.
Conclusion
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/MATTHEW DAVID KIM/Primary Examiner, Art Unit 2483
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