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Found 8 papers, 4 papers with code
G3DR: Generative 3D Reconstruction in ImageNet
We introduce a novel 3D generative method, Generative 3D Reconstruction (G3DR) in ImageNet, capable of generating diverse and high-quality 3D objects from single images, addressing the limitations of existing methods.
AvatarMMC: 3D Head Avatar Generation and Editing with Multi-Modal Conditioning
To the best of our knowledge, our approach is the first to introduce multi-modal conditioning to 3D avatar generation and editing.
AudioSlots: A slot-centric generative model for audio separation
We discuss the results and limitations of our approach in detail, and further outline potential ways to overcome the limitations and directions for future work.
Search for Concepts: Discovering Visual Concepts Using Direct Optimization
Finding an unsupervised decomposition of an image into individual objects is a key step to leverage compositionality and to perform symbolic reasoning.
A Multi-Implicit Neural Representation for Fonts
Fonts are ubiquitous across documents and come in a variety of styles.
Im2Vec: Synthesizing Vector Graphics without Vector Supervision
The current alternative is to use specialized models that require explicit supervision on the vector graphics representation at training time.
Discovering Pattern Structure Using Differentiable Compositing
Patterns, which are collections of elements arranged in regular or near-regular arrangements, are an important graphic art form and widely used due to their elegant simplicity and aesthetic appeal.
SeeThrough: Finding Chairs in Heavily Occluded Indoor Scene Images
Discovering 3D arrangements of objects from single indoor images is important given its many applications including interior design, content creation, etc.
