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Found 11 papers, 4 papers with code
Transforming Radiance Field with Lipschitz Network for Photorealistic 3D Scene Stylization
Simply coupling NeRF with photorealistic style transfer (PST) will result in cross-view inconsistency and degradation of stylized view syntheses.
Generalized One-shot Domain Adaptation of Generative Adversarial Networks
While previous works mainly focus on style transfer, we propose a novel and concise framework to address the \textit{generalized one-shot adaptation} task for both style and entity transfer, in which a reference image and its binary entity mask are provided.
PetsGAN: Rethinking Priors for Single Image Generation
Moreover, we apply our method to other image manipulation tasks (e. g., style transfer, harmonization), and the results further prove the effectiveness and efficiency of our method.
FasterPose: A Faster Simple Baseline for Human Pose Estimation
By the experimental analysis, we find that the HR representation leads to a sharp increase of computational cost, while the accuracy improvement remains marginal compared with the low-resolution (LR) representation.
Towards NIR-VIS Masked Face Recognition
In this paper, we aim to address the challenge of NIR-VIS masked face recognition from the perspectives of training data and training method.
AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing
Face parsing infers a pixel-wise label to each facial component, which has drawn much attention recently.
Ranked #3 on
Face Parsing
on CelebAMask-HQ
FaceX-Zoo: A PyTorch Toolbox for Face Recognition
For example, the production of face representation network desires a modular training scheme to consider the proper choice from various candidates of state-of-the-art backbone and training supervision subject to the real-world face recognition demand; for performance analysis and comparison, the standard and automatic evaluation with a bunch of models on multiple benchmarks will be a desired tool as well; besides, a public groundwork is welcomed for deploying the face recognition in the shape of holistic pipeline.
Edge-aware Graph Representation Learning and Reasoning for Face Parsing
Specifically, we encode a facial image onto a global graph representation where a collection of pixels ("regions") with similar features are projected to each vertex.
Ranked #4 on
Face Parsing
on CelebAMask-HQ
A New Dataset and Boundary-Attention Semantic Segmentation for Face Parsing
The dataset is publicly accessible to the community for boosting the advance of face parsing. 1 Second, a simple yet effective Boundary-Attention Semantic Segmentation (BASS) method is proposed for face parsing, which contains a three-branch network with elaborately developed loss functions to fully exploit the boundary information.
Ranked #8 on
Face Parsing
on LaPa
A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark
Each image is provided with accurate annotation of a 11-category pixel-level label map along with coordinates of 106-point landmarks.
Grand Challenge of 106-Point Facial Landmark Localization
However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.
