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[HTML][HTML] Data augmentation: A comprehensive survey of modern approaches
A Mumuni, F Mumuni - Array, 2022 - Elsevier
To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …
Transformer-based generative adversarial networks in computer vision: A comprehensive survey
Generative adversarial networks (GANs) have been very successful for synthesizing the
images in a given dataset. The artificially generated images by GANs are very realistic. The …
images in a given dataset. The artificially generated images by GANs are very realistic. The …
Mvdream: Multi-view diffusion for 3d generation
We introduce MVDream, a diffusion model that is able to generate consistent multi-view
images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion …
images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion …
Hexplane: A fast representation for dynamic scenes
Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …
approaches build on NeRF and rely on implicit representations. This is slow since it requires …
Rodin: A generative model for sculpting 3d digital avatars using diffusion
This paper presents a 3D diffusion model that automatically generates 3D digital avatars
represented as neural radiance fields (NeRFs). A significant challenge for 3D diffusion is …
represented as neural radiance fields (NeRFs). A significant challenge for 3D diffusion is …
Generative novel view synthesis with 3d-aware diffusion models
We present a diffusion-based model for 3D-aware generative novel view synthesis from as
few as a single input image. Our model samples from the distribution of possible renderings …
few as a single input image. Our model samples from the distribution of possible renderings …
Imagedream: Image-prompt multi-view diffusion for 3d generation
We introduce" ImageDream," an innovative image-prompt, multi-view diffusion model for 3D
object generation. ImageDream stands out for its ability to produce 3D models of higher …
object generation. ImageDream stands out for its ability to produce 3D models of higher …
Stylesdf: High-resolution 3d-consistent image and geometry generation
We introduce a high resolution, 3D-consistent image and shape generation technique which
we call StyleSDF. Our method is trained on single view RGB data only, and stands on the …
we call StyleSDF. Our method is trained on single view RGB data only, and stands on the …
Locally attentional sdf diffusion for controllable 3d shape generation
Although the recent rapid evolution of 3D generative neural networks greatly improves 3D
shape generation, it is still not convenient for ordinary users to create 3D shapes and control …
shape generation, it is still not convenient for ordinary users to create 3D shapes and control …
Advances in neural rendering
Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …
been the focus of decades of research. Traditionally, synthetic images of a scene are …