Interspecies Knowledge Transfer for Facial Keypoint Detection

We present a method for localizing facial keypoints on animals by transferring knowledge gained from human faces. Instead of directly finetuning a network trained to detect keypoints on human faces to animal faces (which is sub-optimal since human and animal faces can look quite different), we propose to first adapt the animal images to the pre-trained human detection network by correcting for the differences in animal and human face shape. We first find the nearest human neighbors for each animal image using an unsupervised shape matching method. We use these matches to train a thin plate spline warping network to warp each animal face to look more human-like. The warping network is then jointly finetuned with a pre-trained human facial keypoint detection network using an animal dataset. We demonstrate state-of-the-art results on both horse and sheep facial keypoint detection, and significant improvement over simple finetuning, especially when training data is scarce. Additionally, we present a new dataset with 3717 images with horse face and facial keypoint annotations.Comment: CVPR 2017 Camera Read

Inefficient Star Formation In Extremely Metal Poor Galaxies

The first galaxies contain stars born out of gas with little or no metals. The lack of metals is expected to inhibit efficient gas cooling and star formation but this effect has yet to be observed in galaxies with oxygen abundance relative to hydrogen below a tenth of that of the Sun. Extremely metal poor nearby galaxies may be our best local laboratories for studying in detail the conditions that prevailed in low metallicity galaxies at early epochs. Carbon Monoxide (CO) emission is unreliable as tracers of gas at low metallicities, and while dust has been used to trace gas in low-metallicity galaxies, low-spatial resolution in the far-infrared has typically led to large uncertainties. Here we report spatially-resolved infrared observations of two galaxies with oxygen abundances below 10 per cent solar, and show that stars form very inefficiently in seven star-forming clumps of these galaxies. The star formation efficiencies are more than ten times lower than found in normal, metal rich galaxies today, suggesting that star formation may have been very inefficient in the early Universe.Comment: Author's version (10 pages, 4 figures). Published in Natur

The Weak Carbon Monoxide Emission In An Extremely Metal Poor Galaxy, Sextans A

Carbon monoxide (CO) is one of the primary coolants of gas and an easily accessible tracer of molecular gas in spiral galaxies but it is unclear if CO plays a similar role in metal poor dwarfs. We carried out a deep observation with IRAM 30 m to search for CO emission by targeting the brightest far-IR peak in a nearby extremely metal poor galaxy, Sextans A, with 7% Solar metallicity. A weak CO J=1-0 emission is seen, which is already faint enough to place a strong constraint on the conversion factor (a_CO) from the CO luminosity to the molecular gas mass that is derived from the spatially resolved dust mass map. The a_CO is at least seven hundred times the Milky Way value. This indicates that CO emission is exceedingly weak in extremely metal poor galaxies, challenging its role as a coolant in these galaxies.Comment: 4 pages, 1 table, 4 figures. ApJL in pres

Properties of CLC According to Replacement Ratio of Cao-CSA Expansive Additive

According to the National Statistical Office\u27s 2019 Population and Housing Survey in August 2020, the number of apartments, including apartments, was about 14 million last year, accounting for 77.2% of all houses, of which 11.287 million were 80.6% of apartments. Based on this change in housing trends, researchers have developed and studied cellular light-weight concrete (CLC) that can be cured at room temperature and normal pressure with advantages such as light weight, insulation, and construction. There have been several studies in Korea, including state-run projects, but they have not been commercialized, but the biggest reason is that stability has not been secured. Therefore, to improve the reliability of CLC that can be cured at normal temperature and pressure, this study attempts to analyze the properties of CLC by incorporating CaO-CSA expansive additive. Based on the drying density of 0.55-0.65 kg/m3, cement, blast furnace slag, animal foaming additive and fiber are utilized to analyze the properties of CLC with CaO-CSA expansive and the results are as follows. By using the CaO-CSA expansive additive, it is determined that the formation of calcium hydroxide and ettringite fills the CLC between the tobermorite layers and the internal structure becomes dense. Currently, based on KS F 2701, the compression strength based on 0.6 items is more than 4.9 MPa, and the strength is about twice as strong as that of the existing CLC, and durability of the CLC are improved by incorporating CaO-CSA expansive additive

HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Clouds

We present a novel deep neural network architecture for end-to-end scene flow estimation that directly operates on large-scale 3D point clouds. Inspired by Bilateral Convolutional Layers (BCL), we propose novel DownBCL, UpBCL, and CorrBCL operations that restore structural information from unstructured point clouds, and fuse information from two consecutive point clouds. Operating on discrete and sparse permutohedral lattice points, our architectural design is parsimonious in computational cost. Our model can efficiently process a pair of point cloud frames at once with a maximum of 86K points per frame. Our approach achieves state-of-the-art performance on the FlyingThings3D and KITTI Scene Flow 2015 datasets. Moreover, trained on synthetic data, our approach shows great generalization ability on real-world data and on different point densities without fine-tuning

Self-supervised Image Denoising with Downsampled Invariance Loss and Conditional Blind-Spot Network

There have been many image denoisers using deep neural networks, which outperform conventional model-based methods by large margins. Recently, self-supervised methods have attracted attention because constructing a large real noise dataset for supervised training is an enormous burden. The most representative self-supervised denoisers are based on blind-spot networks, which exclude the receptive field's center pixel. However, excluding any input pixel is abandoning some information, especially when the input pixel at the corresponding output position is excluded. In addition, a standard blind-spot network fails to reduce real camera noise due to the pixel-wise correlation of noise, though it successfully removes independently distributed synthetic noise. Hence, to realize a more practical denoiser, we propose a novel self-supervised training framework that can remove real noise. For this, we derive the theoretic upper bound of a supervised loss where the network is guided by the downsampled blinded output. Also, we design a conditional blind-spot network (C-BSN), which selectively controls the blindness of the network to use the center pixel information. Furthermore, we exploit a random subsampler to decorrelate noise spatially, making the C-BSN free of visual artifacts that were often seen in downsample-based methods. Extensive experiments show that the proposed C-BSN achieves state-of-the-art performance on real-world datasets as a self-supervised denoiser and shows qualitatively pleasing results without any post-processing or refinement

Ginkgo biloba extract (EGb761) inhibits mitochondria-dependent caspase pathway and prevents apoptosis in hypoxia-reoxygenated cardiomyocytes

Background: EGb761 is a standard extract from the leaves of Ginkgo biloba (Yinxing) containing ginkgo-flavone glycosides and terpenoid. The flavonoid components of EGb761 scavenge free radicals and protect myocardia from ischemia-reperfusion injury. The present study aims to determine the effects of the active compounds of EGb761 on mitochondria-dependent caspase pathway.Methods: Cardiomyocytes were exposed to 24 hours of hypoxia and four hours of reoxygenation, and pretreated with EGb761, bilobalide and quertcetin. By using immunoblot, immunofluorescent, biochemical and flow cytometry techniques, we compared the effects of EGb761 and its representative constituents including quercetin and bilobalides on regulating mitochondria-dependent caspases signal pathway and apoptotic cell death in the hypoxia-reoxygenated cardiomyocytes.Results: Pretreatment with EGb761 significantly inhibited the release of cytochrome c from mitochondria, the expression of caspase-3, cleavage activities of caspases and attenuated apoptotic cell death. The effects of quercetin on the release of cytochrome c, the cleavage activities of caspases and cell death were similar to those of EGb761 but better than those of bilobalide.Conclusion: The antioxidant constituents of EGb761 such as quercetin contribute to the cardioprotective effects of EGb761 and inhibit the mitochondria-dependent caspase pathway. It is possible that the mitochondria-dependent caspase pathway may be one of the molecular targets of EGb761 against myocardial ischemia-reperfusion injury. © 2011 Shen et al; licensee BioMed Central Ltd.published_or_final_versio