Sparse3D: Distilling Multiview-Consistent Diffusion for Object Reconstruction from Sparse Views

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained diffusion priors into 3D representations using score distillation sampling (SDS), these methods often struggle to simultaneously achieve high-quality, consistent, and detailed results for both novel-view synthesis (NVS) and geometry. In this work, we present Sparse3D, a novel 3D reconstruction method tailored for sparse view inputs. Our approach distills robust priors from a multiview-consistent diffusion model to refine a neural radiance field. Specifically, we employ a controller that harnesses epipolar features from input views, guiding a pre-trained diffusion model, such as Stable Diffusion, to produce novel-view images that maintain 3D consistency with the input. By tapping into 2D priors from powerful image diffusion models, our integrated model consistently delivers high-quality results, even when faced with open-world objects. To address the blurriness introduced by conventional SDS, we introduce the category-score distillation sampling (C-SDS) to enhance detail. We conduct experiments on CO3DV2 which is a multi-view dataset of real-world objects. Both quantitative and qualitative evaluations demonstrate that our approach outperforms previous state-of-the-art works on the metrics regarding NVS and geometry reconstruction

Photopic pupil size change in myopic orthokeratology and its influence on axial length elongation

AIM: To explore the photopic pupil size behavior in myopic children undergoing overnight orthokeratology (ortho-k) over 1-year period and its effects on the axial elongation. METHODS: A total of 202 Chinese myopic children were enrolled in this prospective clinical trial. Ninety-five subjects in ortho-k group and eighty-eight subjects in spectacle group completed the 1-year study. Axial length (AL) was measured before enrollment and every 6mo after the start of ortho-k. The photopic pupil diameter (PPD) was determined using the Pentacam AXL and measured in an examination room with lighting of 300-310 Lx. Stepwise multiple linear regression analysis was used to identify variables contribution to axial elongation. RESULTS: Compared with spectacle group, the average 1-year axial elongation was significantly slower in the ortho-k group (0.25±0.27 vs 0.44±0.23 mm, P0.05, Bonferroni correction). The 4.81 mm PPD may be a possible cutoff point in the ortho-k group. Subjects with PPD below or equal to 4.81 mm tended to have smaller axial elongation compared to subjects with PPD above 4.81 mm after 1-year period (t=-3.09, P=0.003). In ortho-k group, univariate analyses indicated that those with older age, greater degree of myopia, longer AL, smaller baseline PPD (PPDbaseline) experienced a smaller change in AL. In multivariate analyses, older age, greater AL and smaller PPDbaseline were associated with smaller increases in AL. In spectacle group, PPD tended to be stable (P>0.05, Bonferroni correction) and did not affect axial growth. CONCLUSION: PPDs experience significantly decreases at 1-month and 3-month ortho-k treatment. Children with smaller PPD tend to experience slower axial elongation and may benefit more from ortho-k

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Research on the application of active sound barriers for the transformer noise abatement

Sound barriers are a type of measure most commonly used in the noise abatement of transformers. In the noise abatement project of substations, the design of sound barriers is restrained by the portal frames which are used to hold up outgoing lines from the main transformers, which impacts the noise reduction effect. If active sound barriers are utilized in these places, the noise diffraction of sound barriers can be effectively reduced. At a 110kV Substation, an experiment using a 15-channel active sound barrier has been carried out. The result of the experiment shows that the mean noise reduction value (MNRV) of the noise measuring points at the substation boundary are 1.5 dB (A). The effect of the active noise control system is impacted by the layout of the active noise control system, the acoustic environment on site and the spectral characteristic of the target area

Research on the application of active sound barriers for the transformer noise abatement

Sound barriers are a type of measure most commonly used in the noise abatement of transformers. In the noise abatement project of substations, the design of sound barriers is restrained by the portal frames which are used to hold up outgoing lines from the main transformers, which impacts the noise reduction effect. If active sound barriers are utilized in these places, the noise diffraction of sound barriers can be effectively reduced. At a 110kV Substation, an experiment using a 15-channel active sound barrier has been carried out. The result of the experiment shows that the mean noise reduction value (MNRV) of the noise measuring points at the substation boundary are 1.5 dB (A). The effect of the active noise control system is impacted by the layout of the active noise control system, the acoustic environment on site and the spectral characteristic of the target area

Research on the application of active sound barriers for the transformer noise abatement

Sound barriers are a type of measure most commonly used in the noise abatement of transformers. In the noise abatement project of substations, the design of sound barriers is restrained by the portal frames which are used to hold up outgoing lines from the main transformers, which impacts the noise reduction effect. If active sound barriers are utilized in these places, the noise diffraction of sound barriers can be effectively reduced. At a 110kV Substation, an experiment using a 15-channel active sound barrier has been carried out. The result of the experiment shows that the mean noise reduction value (MNRV) of the noise measuring points at the substation boundary are 1.5 dB (A). The effect of the active noise control system is impacted by the layout of the active noise control system, the acoustic environment on site and the spectral characteristic of the target area

Sparse3D: Distilling Multiview-Consistent Diffusion for Object Reconstruction from Sparse Views

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained diffusion priors into 3D representations using score distillation sampling (SDS), these methods often struggle to simultaneously achieve high-quality, consistent, and detailed results for both novel-view synthesis (NVS) and geometry. In this work, we present Sparse3D, a novel 3D reconstruction method tailored for sparse view inputs. Our approach distills robust priors from a multiview-consistent diffusion model to refine a neural radiance field. Specifically, we employ a controller that harnesses epipolar features from input views, guiding a pre-trained diffusion model, such as Stable Diffusion, to produce novel-view images that maintain 3D consistency with the input. By tapping into 2D priors from powerful image diffusion models, our integrated model consistently delivers high-quality results, even when faced with open-world objects. To address the blurriness introduced by conventional SDS, we introduce the category-score distillation sampling (C-SDS) to enhance detail. We conduct experiments on CO3DV2 which is a multi-view dataset of real-world objects. Both quantitative and qualitative evaluations demonstrate that our approach outperforms previous state-of-the-art works on the metrics regarding NVS and geometry reconstruction