High-fidelity human avatars from a single RGB camera

In this paper, we propose a coarse-to-fine framework to reconstruct a personalized high-fidelity human avatar from a monocular video. To deal with the misalignment problem caused by the changed poses and shapes in different frames, we design a dynamic surface network to recover pose-dependent surface deformations, which help to decouple the shape and texture of the person. To cope with the complexity of textures and generate photo-realistic results, we propose a reference-based neural rendering network and exploit a bottom-up sharpening-guided fine-tuning strategy to obtain detailed textures. Our frame-work also enables photo-realistic novel view/pose syn-thesis and shape editing applications. Experimental re-sults on both the public dataset and our collected dataset demonstrate that our method outperforms the state-of-the-art methods. The code and dataset will be available at http://cic.tju.edu.cn/faculty/likun/projects/HF-Avatar

Learning to infer inner-body under clothing from monocular video

Accurately estimating the human inner-body under clothing is very important for body measurement, virtual try-on and VR/AR applications. In this paper, we propose the first method to allow everyone to easily reconstruct their own 3D inner-body under daily clothing from a self-captured video with the mean reconstruction error of 0.73 cm within 15 s. This avoids privacy concerns arising from nudity or minimal clothing. Specifically, we propose a novel two-stage framework with a Semantic-guided Undressing Network (SUNet) and an Intra-Inter Transformer Network (IITNet). SUNet learns semantically related body features to alleviate the complexity and uncertainty of directly estimating 3D inner-bodies under clothing. IITNet reconstructs the 3D inner-body model by making full use of intra-frame and inter-frame information, which addresses the misalignment of inconsistent poses in different frames. Experimental results on both public datasets and our collected dataset demonstrate the effectiveness of the proposed method. The code and dataset is available for research purposes at http://cic.tju.edu.cn/faculty/likun/projects/Inner-Body

Sclerotinia sclerotiorum SsCut1 Modulates Virulence and Cutinase Activity

The plant cuticle is one of the protective layers of the external surface of plant tissues. Plants use the cuticle layer to reduce water loss and resist pathogen infection. Fungi release cell wall-degrading enzymes to destroy the epidermis of plants to achieve the purpose of infection. Sclerotinia sclerotiorum secretes a large amount of cutinase to disrupt the cuticle layer of plants during the infection process. In order to further understand the role of cutinase in the pathogenic process of S. sclerotiorum, the S. sclerotiorum cutinsae 1 (SsCut1) gene was cloned and analyzed. The protein SsCut1 contains the conserved cutinase domain and a fungal cellulose-binding domain. RT-qPCR results showed that the expression of SsCut1 was significantly upregulated during infection. Split-Marker recombination was utilized for the deletion of the SsCut1 gene, ΔSsCut1 mutants showed reduced cutinase activity and virulence, but the deletion of the SsCut1 gene had no effect on the growth rate, colony morphology, oxalic acid production, infection cushion formation and sclerotial development. Complementation with the wild-type SsCut1 allele restored the cutinase activity and virulence to the wild-type level. Interestingly, expression of SsCut1 in plants can trigger defense responses, but it also enhanced plant susceptibility to SsCut1 gene knock-out mutants. Taken together, our finding demonstrated that the SsCut1 gene promotes the virulence of S. sclerotiorum by enhancing its cutinase activity

Association of serum retinol concentration with normal-tension glaucoma.

OBJECTIVES: To evaluate the association between serum retinol concentration and normal-tension glaucoma (NTG). METHODS: A total of 345 study subjects were recruited in a prospective cross-sectional study: 101 patients with NTG, 106 patients with high-pressure primary open-angle glaucoma (POAG) and 138 healthy control subjects. Serum retinol concentration in fasting blood samples was determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). All study subjects were given complete ophthalmic examinations and diagnosed by two glaucoma sub-specialists. RESULTS: Serum retinol concentrations in NTG, POAG, and controls were 338.90 ± 103.23 ng/mL, 405.22 ± 114.12 ng/mL, and 408.84 ± 122.36 ng/mL respectively. NTG patients had lower serum retinol concentrations than POAG (p < 0.001) or healthy controls (p < 0.001). There was no statistical difference between the POAG and healthy controls (p = 0.780). Higher proportion of NTG patients (37.6%) than POAG (17.9%) or controls (21.7%) had serum retinol concentrations lower than 300 ng/mL. Serum retinol was positively correlated with optic nerve sheath diameter (ONSD) (r = 0.349, p = 0.001) in glaucoma patients and not associated with any other demographic features or ophthalmic biometric parameters in the NTG patients. Multivariate logistic regression showed that serum retinol (OR = 0.898, 95CI%: 0.851-0.947) was associated with incident NTG. CONCLUSIONS: NTG patients had lower serum retinol concentrations. Serum retinol uniquely associated with NTG makes it a new potential option for the diagnosis and treatment of the disease