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 Objections
Claim 1 is objected to because of the following informalities: Claim 1 recites the term "denoismg;" the term is misspelled and is suggested to be spelled "denoising". Appropriate correction is required.
Claims 4 objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim cannot depend from any other multiple dependent claim. See MPEP § 608.01(n). Accordingly, the claims have not been further treated on the merits.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being incomplete for omitting essential elements, such omission amounting to a gap between the elements. See MPEP § 2172.01. The omitted elements are: the synthetic images represent novel views of the three-dimensional scene.
By omitting that the synthetic images represent novel views of the three-dimensional scene, claim 1 fails to claim the subject matter that the inventor or a joint inventor regards as the invention. The omitted matter is essential to the invention based at least on the claim 1 preamble “A computer-implemented method to perform novel view synthesis of a three-dimensional scene with a machine-learned diffusion model…” The preamble defines purpose of the invention as a method to perform novel view synthesis; however, the body of the claim does not address this concept.
Further, the specification supports that the omitted matter is essential to the invention. In the field of the invention in the specification, it states “the present disclosure relates to systems and methods to perform novel view synthesis of a three-dimensional scene with a machine-learned diffusion model,” (specification, para [0002]). Figures 1B and 1C show that the synthetic images represent novel views (specification, para [0052]; Fig 1B; Fig 1C). The detailed description in the specification recites “any number of synthetic images representing novel views of the scene can be generated,” (specification, para [0065]).
Claims 2-11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being incomplete for omitting essential elements, such omission amounting to a gap between the elements. See MPEP § 2172.01.
Claims 2-11 are rejected due to being dependent on claim 1.
Allowable Subject Matter
The following claim 1 drafted by the examiner and considered to distinguish patentably over the art of record in this application, is presented to applicant for consideration:
A computer-implemented method to perform novel view synthesis of a three- dimensional scene with a machine-learned diffusion model, the method comprising: for each of one or more iterations:
obtaining, by a computing system comprising one or more computing devices, an input comprising data descriptive of an input pose;
processing, by the computing system, the input with the machine-learned diffusion model to generate a synthetic image of the three-dimensional scene from the input pose, the synthetic image representing a novel view of the three-dimensional scene;
wherein the machine-learned diffusion model comprises a plurality of denoising steps configured to respectively receive a plurality of conditioning images; and wherein processing, by the computing system, the input with the machine- learned diffusion model to generate the synthetic image comprises, for each of at least two of the plurality of denoising steps:
accessing, by the computing system, an image set that comprises a plurality of images that depict the three-dimensional scene from a plurality of poses; and
sampling, by the computing system, a sampled image from the image set to serve as the conditioning image for such denoising step.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yu et al., “pixelNeRF: Neural Radiance Fields from One or Few Images”, 30 May 2021, Arxiv, pages 1-20 – Teaches the state of the art of novel view synthesis of a three-dimensional scene with machine learning, like that of claim 1
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERICA G THERKORN whose telephone number is (571)272-2939. The examiner can normally be reached Monday - Friday 9:00am - 5:00pm.
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/ERICA G THERKORN/Examiner, Art Unit 2618
/DEVONA E FAULK/Supervisory Patent Examiner, Art Unit 2618
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