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Found 8 papers, 3 papers with code
MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing
To address this limitation, we propose \textbf{MaTe3D}: mask-guided text-based 3D-aware portrait editing.
VividTalk: One-Shot Audio-Driven Talking Head Generation Based on 3D Hybrid Prior
Audio-driven talking head generation has drawn much attention in recent years, and many efforts have been made in lip-sync, expressive facial expressions, natural head pose generation, and high video quality.
HAVE-FUN: Human Avatar Reconstruction from Few-Shot Unconstrained Images
As for human avatar reconstruction, contemporary techniques commonly necessitate the acquisition of costly data and struggle to achieve satisfactory results from a small number of casual images.
Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On
Since traditional warping-based texture generation methods require a significant number of control points to be manually selected for each type of garment, which can be a time-consuming and tedious process.
DART: Articulated Hand Model with Diverse Accessories and Rich Textures
Unity GUI is also provided to generate synthetic hand data with user-defined settings, e. g., pose, camera, background, lighting, textures, and accessories.
Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis
To address this challenge, we propose Multi-View Consistent Generative Adversarial Networks (MVCGAN) for high-quality 3D-aware image synthesis with geometry constraints.
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
Deepfake defense not only requires the research of detection but also requires the efforts of generation methods.
Ranked #1 on
Face Swapping
on FaceForensics++
A SPIKING SEQUENTIAL MODEL: RECURRENT LEAKY INTEGRATE-AND-FIRE
Stemming from neuroscience, Spiking neural networks (SNNs), a brain-inspired neural network that is a versatile solution to fault-tolerant and energy efficient information processing pertains to the ”event-driven” characteristic as the analogy of the behavior of biological neurons.
