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Found 9 papers, 1 papers with code
FiVA: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models
In this work, we formulate a more effective approach to decompose the aesthetics of a picture into specific visual attributes, allowing users to apply characteristics such as lighting, texture, and dynamics from different images.
Flying with Photons: Rendering Novel Views of Propagating Light
Combined with this dataset, we introduce an efficient neural volume rendering framework based on the transient field.
Orthogonal Adaptation for Modular Customization of Diffusion Models
In this paper, we address a new problem called Modular Customization, with the goal of efficiently merging customized models that were fine-tuned independently for individual concepts.
Gaussian Shell Maps for Efficient 3D Human Generation
Instead of rasterizing the shells directly, we sample 3D Gaussians on the shells whose attributes are encoded in the texture features.
State of the Art on Diffusion Models for Visual Computing
The field of visual computing is rapidly advancing due to the emergence of generative artificial intelligence (AI), which unlocks unprecedented capabilities for the generation, editing, and reconstruction of images, videos, and 3D scenes.
Instant Continual Learning of Neural Radiance Fields
Neural radiance fields (NeRFs) have emerged as an effective method for novel-view synthesis and 3D scene reconstruction.
Compositional 3D Scene Generation using Locally Conditioned Diffusion
Designing complex 3D scenes has been a tedious, manual process requiring domain expertise.
3D Neural Field Generation using Triplane Diffusion
Diffusion models have emerged as the state-of-the-art for image generation, among other tasks.
Adaptive Gating for Single-Photon 3D Imaging
Single-photon avalanche diodes (SPADs) are growing in popularity for depth sensing tasks.
