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Found 6 papers, 3 papers with code
StyleGaussian: Instant 3D Style Transfer with Gaussian Splatting
We introduce StyleGaussian, a novel 3D style transfer technique that allows instant transfer of any image's style to a 3D scene at 10 frames per second (fps).
DivAvatar: Diverse 3D Avatar Generation with a Single Prompt
We design DivAvatar, a novel framework that generates diverse avatars, empowering 3D creatives with a multitude of distinct and richly varied 3D avatars from a single text prompt.
AI-Generated Images as Data Source: The Dawn of Synthetic Era
The advancement of visual intelligence is intrinsically tethered to the availability of large-scale data.
Pose-Free Neural Radiance Fields via Implicit Pose Regularization
However, as the pose estimator is trained with only rendered images, the pose estimation is usually biased or inaccurate for real images due to the domain gap between real images and rendered images, leading to poor robustness for the pose estimation of real images and further local minima in joint optimization.
Weakly Supervised 3D Open-vocabulary Segmentation
Open-vocabulary segmentation of 3D scenes is a fundamental function of human perception and thus a crucial objective in computer vision research.
StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields
In addition, it transforms the grid features according to the reference style which directly leads to high-quality zero-shot style transfer.
