Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions, textures, and poses of the generated face images. However, these methods focus on 2D image generative models, which are prone to producing inconsistent face images under large expression and pose changes. In this paper, we propose a new NeRF-based conditional 3D face synthesis framework, which enables 3D controllability over the generated face images by imposing explicit 3D conditions from 3D face priors. At its core is a conditional Generative Occupancy Field (cGOF) that effectively enforces the shape of the generated face to commit to a given 3D Morphable Model (3DMM) mesh. To achieve accurate control over fine-grained 3D face shapes of the synthesized image, we additionally incorporate a 3D landmark loss as well as a volume warping loss into our synthesis algorithm. Experiments validate the effectiveness of the proposed method, which is able to generate high-fidelity face images and shows more precise 3D controllability than state-of-the-art 2D-based controllable face synthesis methods. Find code and demo at https://keqiangsun.github.io/projects/cgof

CGOF++: Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions, textures, and poses of the generated face images. However, previous methods focus on controllable 2D image generative models, which are prone to producing inconsistent face images under large expression and pose changes. In this paper, we propose a new NeRF-based conditional 3D face synthesis framework, which enables 3D controllability over the generated face images by imposing explicit 3D conditions from 3D face priors. At its core is a conditional Generative Occupancy Field (cGOF++) that effectively enforces the shape of the generated face to conform to a given 3D Morphable Model (3DMM) mesh, built on top of EG3D [1], a recent tri-plane-based generative model. To achieve accurate control over fine-grained 3D face shapes of the synthesized images, we additionally incorporate a 3D landmark loss as well as a volume warping loss into our synthesis framework. Experiments validate the effectiveness of the proposed method, which is able to generate high-fidelity face images and shows more precise 3D controllability than state-of-the-art 2D-based controllable face synthesis methods.Comment: This article is an extension of the NeurIPS'22 paper arXiv:2206.0836

Receiver-Driven Adaptive Enhancement Layer Switching Algorithm for Scalable Video Transmission Over Link-adaptive Networks

A receiver-driven adaptive layer switching algorithm is proposed for adapting the video bitrate to match the achievable network throughput. It relies on a QoS-constrained equivalent bandwidth estimator employed at the receiver, which is used for triggering the adjustment of video layers at the video source. Simulations are conducted to illustrate its efficiency by showing that it is capable of accommodating different channel qualities without their prior knowledge

Femtosecond Laser-Induced Phase Transformation on Single-Crystal 6H-SiC

Silicon carbide (SiC) is widely used in many research fields because of its excellent properties. The femtosecond laser has been proven to be an effective method for achieving high-quality and high-efficiency SiC micromachining. In this article, the ablation mechanism irradiated on different surfaces of 6H-SiC by a single pulse under different energies was investigated. The changes in material elements and the geometric spatial distribution of the ablation pit were analyzed using micro-Raman spectroscopy, Energy Dispersive Spectrum (EDS), and an optical microscope, respectively. Moreover, the thresholds for structural transformation and modification zones of 6H-SiC on different surfaces were calculated based on the diameter of the ablation pits created by a femtosecond laser at different single-pulse energies. Experimental results show that the transformation thresholds of the Si surface and the C surface are 5.60 J/cm2 and 6.40 J/cm2, corresponding to the modification thresholds of 2.26 J/cm2 and 2.42 J/cm2, respectively. The Raman and EDS results reveal that there are no phase transformations or material changes on different surfaces of 6H-SiC at low energy, however, decomposition and oxidation occur and then accumulate into dense new phase material under high-energy laser irradiation. We found that the distribution of structural phase transformation is uneven from the center of the spot to the edge. The content of this research reveals the internal evolution mechanism of high-quality laser processing of hard material 6H-SiC. We expect that this research will contribute to the further development of SiC-based MEMS devices

Flexible and Biocompatible Silk Fiber-Based Composite Phase Change Material for Personal Thermal Management

Phase change materials (PCMs) are regarded as an effective passive personal thermal management strategy. However, the preparation of flexible and biocompatible PCMs remains a great challenge. In this study, a silk fiber (SF)-based composite PCM for wearable personal thermal management was prepared using renewable natural silkworm cocoons and biocompatible capric acid (CA). The SF/CA composite PCM is flexible, biocompatible, and dyeable. The results show that the SF and CA are physically bonded, and the crystal structure of CA is not influenced by SF. The melting phase change enthalpy and temperature of the SF/CA composite PCM are 123.4 J/g and 30.6 °C, respectively. It has excellent shape stability, thermal stability, and cycling stability. Particularly, the SF/CA composite PCM has excellent performance for wearable personal thermal management under three scenarios including variable temperature mode, isothermal mode, and light irradiation mode. It can also reduce the temperature fluctuation of the human body in a hot or cold environment. Therefore, the SF/CA composite PCM has bright application prospects for wearable personal thermal management in hot and cold environments

Flexible and Biocompatible Silk Fiber-Based Composite Phase Change Material for Personal Thermal Management

Phase change materials (PCMs) are regarded as an effective passive personal thermal management strategy. However, the preparation of flexible and biocompatible PCMs remains a great challenge. In this study, a silk fiber (SF)-based composite PCM for wearable personal thermal management was prepared using renewable natural silkworm cocoons and biocompatible capric acid (CA). The SF/CA composite PCM is flexible, biocompatible, and dyeable. The results show that the SF and CA are physically bonded, and the crystal structure of CA is not influenced by SF. The melting phase change enthalpy and temperature of the SF/CA composite PCM are 123.4 J/g and 30.6 °C, respectively. It has excellent shape stability, thermal stability, and cycling stability. Particularly, the SF/CA composite PCM has excellent performance for wearable personal thermal management under three scenarios including variable temperature mode, isothermal mode, and light irradiation mode. It can also reduce the temperature fluctuation of the human body in a hot or cold environment. Therefore, the SF/CA composite PCM has bright application prospects for wearable personal thermal management in hot and cold environments