Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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.
Claims 1, 7-8, 14 and 20 are rejected under 35 U.S.C. 102(1)(1) as being anticipated by Zhang (“SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation”, CVPR June 2023)
As for claim 1, Zhang teaches
a method for video generation in machine learning, the method comprising:
encoding an input audio into a plurality of audio features (ch 3.2 par 3 “audio feature of each frame is a 0.2 mel-spectrogram”; ch 4.1 par 1 “the input audios are .. transformed to mel-spectrograms”), and encoding a first pose state into a first pose feature; (Fig 2 p(1..n) are pose features and thus p1 is a “first pose feature”)
constructing a first latent encoding having the audio features and the first pose feature (ch 3.2 PoseVAE, Fig 4 section “Test” – Decoder D receives the Gaussian-sampled head pose parameters derived from p1..t, as well as the “conditions” that include the audio features as discussed earlier; the combined input into the Decoder which includes audio and sampled head-pose features can be called “latent encodings” and the pair corresponding to frame 1 of the frames 1..t is “first encoding”)
encoding a second pose state into a second pose features, and constructing a second latent encoding having the audio features and the second pose feature; (analogously as discussed above, coefficients corresponding to frames 2 through t can be called “second” etc)
decoding features in the first latent encoding in to first sequences, and decoding features in the second latent encoding in to second sequences (Fig 4 decoder D, producing “delta-p1..t” from the above-discussed inputs); and
rendering a video based on the first sequences, (Fig 5, ch 3.3 rendering video from above-discussed inputs)
wherein the first pose feature, the second pose feature, and each of the audio features respectively corresponds to one frame (NOTE the claim does require that all of the recited components correspond to the same frame; thus each of the features p1, p2, a1 etc each correspond to a frame as indexed by numbers 1, 2 etc); and
the first pose state is different from the second pose state (from Fig 1, we can easily see that poses in most adjacent frames are different from each other)
As for independent claims 8 and 14, please see discussion of analogous claim 1 above.
As for claims 7, 20, Zhang teaches
the first pose state is determined from a first video clip sampled from a video space, the second pose state is determined from a second video clip sampled from the video space, and the first video clip is different from the second video clip (Zhang ch 4.1 teaches “we select 1890 aligned videos and audios of 46 subjects to train..”; it inherently follows that at least for some of the subjects, there are multiple video clips, i.e. “first and second video clip”)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 disclosed as set forth in section 102 of this title, 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.
Claims 2-3, 9-10 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Aranda (“Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality” Electronics 2021)
As for claims 2, 9, 15, Zhang does not explicitly teach
applying a first noise to the first pose state before encoding the first pose state
However Zhang teaches, ch 4.1 Datasets, that the videos utilized for evaluation are downsampled to 256x256 size. Aranda ch 7.1 compares various downsampling techniques such as elastic, non-elastic and fixed-rate sampling, and teaches that even the more advanced of the discussed techniques introduce artifacts, i.e. “noise”, into the images. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Zhang and Aranda as they both pertain to the art of downsampling images. One of ordinary skill in the art at the time of the invention would have been motivated to combine said teachings, in order to evaluate the quality of training images, when they’re being downsampled.
As for claims 3, 10, 16, Zhang does not explicitly teach
applying a second noise to the second pose state before encoding the second pose state.
However please see discussion of obviousness and motivation to combine, of analogous features in claims 2, 9 and 15, above.
Allowable Subject Matter
Claims 4-5, 11-12 and 17-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is the Examiner’s statement of reasons for indicating allowable subject matter:
Features in the claim are not found in prior art, in conjunction with the entire scope of the claim. Specifically,
duplicating a pose feature into a plurality of features and respectively concatenating each of the audio features and each of the duplicated features.
Claims 6, 13, 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is the Examiner’s statement of reasons for indicating allowable subject matter:
Features in the claim are not found in prior art, in conjunction with the entire scope of the claim. Specifically,
replacing the first pose state with a third pose state corresponds to the last sequence for a next iteration in a testing phase.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK ROZ whose telephone number is (571)270-3382. The examiner can normally be reached on 9AM-5PM M-F.
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/MARK ROZ/
Primary Examiner, Art Unit 2669
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