FLNeRF: 3D Facial Landmarks Estimation in Neural Radiance Fields

This paper presents the first significant work on directly predicting 3D face landmarks on neural radiance fields (NeRFs), without using intermediate representations such as 2D images, depth maps, or point clouds. Our 3D coarse-to-fine Face Landmarks NeRF (FLNeRF) model efficiently samples from the NeRF on the whole face with individual facial features for accurate landmarks. To mitigate the limited number of facial expressions in the available data, local and non-linear NeRF warp is applied at facial features in fine scale to simulate large emotions range, including exaggerated facial expressions (e.g., cheek blowing, wide opening mouth, eye blinking), for training FLNeRF. With such expression augmentation, our model can predict 3D landmarks not limited to the 20 discrete expressions given in the data. Robust 3D NeRF facial landmarks contribute to many downstream tasks. As an example, we modify MoFaNeRF to enable high-quality face editing and swapping using face landmarks on NeRF, allowing more direct control and wider range of complex expressions. Experiments show that the improved model using landmarks achieves comparable to better results.Comment: Hao Zhang and Tianyuan Dai contributed equally. Project website: https://github.com/ZHANG1023/FLNeR

FDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models

The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries. In this paper, we propose Face Diffusion NeRF (FDNeRF), a new generative method to reconstruct high-quality Face NeRFs from single images, complete with semantic editing and relighting capabilities. FDNeRF utilizes high-resolution 3D GAN inversion and expertly trained 2D latent-diffusion model, allowing users to manipulate and construct Face NeRFs in zero-shot learning without the need for explicit 3D data. With carefully designed illumination and identity preserving loss, as well as multi-modal pre-training, FD-NeRF offers users unparalleled control over the editing process enabling them to create and edit face NeRFs using just single-view images, text prompts, and explicit target lighting. The advanced features of FDNeRF have been designed to produce more impressive results than existing 2D editing approaches that rely on 2D segmentation maps for editable attributes. Experiments show that our FDNeRF achieves exceptionally realistic results and unprecedented flexibility in editing compared with state-of-the-art 3D face reconstruction and editing methods. Our code will be available at https://github.com/BillyXYB/FDNeRF

Apigenin Ameliorates Hyperuricemia and Renal Injury through Regulation of Uric Acid Metabolism and JAK2/STAT3 Signaling Pathway

Hyperuricemia (HUA) is a kind of metabolic disease with high incidence that still needs new countermeasures. Apigenin has uric-lowering and kidney-protective activities, but how apigenin attenuates HUA and renal injury remains largely unexploited. To this end, an acute HUA mouse model was established by intraperitoneal injection of potassium oxazinate and oral administration with hypoxanthine for 7 consecutive days. Apigenin intervention decreased serum uric acid (UA), creatinine (CRE), blood urea nitrogen (BUN), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor (TNF-α), interleukin-18 (IL-18), liver xanthine oxidase (XOD), and urine protein levels, and increased serum interleukin-10 (IL-10) and urine UA and CRE levels in HUA mice. Moreover, administration of apigenin to HUA mice prevented renal injury, decreased renal glucose transporter 9 (GLUT9) and urate anion transporter 1 (URAT1) levels, and increased renal organic anion transporter 1 (OAT1). These alterations were associated with an inhibition of IL-6, phospho-janus kinase 2 (P-JAK2), phospho-signal transducer, and activator of transcription 3 (P-STAT3), and suppression of cytokine signaling 3 (SOCS3) expression in the kidneys. Additionally, the molecular docking results showed that apigenin had strong binding capacity with UA transporters and JAK2 proteins. In summary, apigenin could improve UA metabolism and attenuate renal injury through inhibiting UA production, promoting excretion, and suppressing the JAK2/STAT3 signaling pathway in HUA mice. The results suggest that apigenin may be a suitable drug candidate for management of HUA and its associated renal injury

Correction: Liu et al. Apigenin Ameliorates Hyperuricemia and Renal Injury through Regulation of Uric Acid Metabolism and JAK2/STAT3 Signaling Pathway. <i>Pharmaceuticals</i> 2022, <i>15</i>, 1442

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